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Find link is a tool written by Edward Betts.searching for Learning rule 242 found (253 total)
alternate case: learning rule
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a learning rule, by which the synaptic efficacy is altered by voltages applied to the terminals of the device. An example of such a learning rule isBCPNN (2,455 words) [view diff] exact match in snippet view article find links to article
mining, for example for discovery of adverse drug reactions. The BCPNN learning rule has also been used to model biological synaptic plasticity and intrinsicUnsupervised learning (2,770 words) [view diff] exact match in snippet view article find links to article
learning also employs other methods including: Hopfield learning rule, Boltzmann learning rule, Contrastive Divergence, Wake Sleep, Variational InferencePhi Kappa Phi (2,381 words) [view diff] case mismatch in snippet view article find links to article
Love of Learning Rules all Mankind", was changed to "Let the Love of Learning Rule Mankind" due to membership insistence that the former was, in the wordsDelta rule (1,104 words) [view diff] exact match in snippet view article find links to article
In machine learning, the delta rule is a gradient descent learning rule for updating the weights of the inputs to artificial neurons in a single-layerSynaptic weight (528 words) [view diff] exact match in snippet view article find links to article
by j {\displaystyle j} . The synaptic weight is changed by using a learning rule, the most basic of which is Hebb's rule, which is usually stated inWin–stay, lose–switch (282 words) [view diff] exact match in snippet view article find links to article
prisoner's dilemma in order to model the evolution of altruism. The learning rule bases its decision only on the outcome of the previous play. OutcomesRishikesh Narayanan (906 words) [view diff] case mismatch in snippet view article find links to article
Regulating the Sliding Modification Threshold in a BCM-Like Synaptic Learning Rule". J Neurophysiol. 104 (2): 1020–33. doi:10.1152/jn.01129.2009. PMC 2934916International Conference on Machine Learning (377 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineParallel processing (psychology) (2,080 words) [view diff] no match in snippet view article
In psychology, parallel processing is the ability of the brain to simultaneously process incoming stimuli of differing quality. Parallel processing isSemantic space (576 words) [view diff] no match in snippet view article find links to article
create either rule-based NLP systems or training corpora for model learning. Rule-based and machine learning based models are fixed on the keyword levelInternational Conference on Learning Representations (272 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineAmos Storkey (613 words) [view diff] case mismatch in snippet view article find links to article
threshold nodes and Storkey developed what became known as the "Storkey Learning Rule". Subsequently, he has worked on approximate Bayesian methods, machineComputational learning theory (865 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSelf-play (504 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineCURE algorithm (788 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineWinner-take-all (computing) (1,241 words) [view diff] exact match in snippet view article
the Instar learning rule. All other weights remain unchanged. The k-winners-take-all rule is similar, except that the Instar learning rule is appliedFeedforward neural network (2,242 words) [view diff] exact match in snippet view article find links to article
1137–1155. Auer, Peter; Harald Burgsteiner; Wolfgang Maass (2008). "A learning rule for very simple universal approximators consisting of a single layerDifferentiable programming (1,014 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGated recurrent unit (1,278 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineStructured prediction (773 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRelevance vector machine (425 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineStorage (memory) (3,689 words) [view diff] exact match in snippet view article
learning is represented by the Hebbian learning rule. Anderson shows that combination of Hebbian learning rule and McCulloch–Pitts dynamical rule allowGraphical model (1,278 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineWaveNet (1,699 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineState–action–reward–state–action (716 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRule-based system (1,202 words) [view diff] case mismatch in snippet view article find links to article
rule-based languages Learning classifier system Rule-based machine learning Rule-based modeling Crina Grosan; Ajith Abraham (29 July 2011). IntelligentFeature (machine learning) (1,027 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineHuman-in-the-loop (978 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineProbably approximately correct learning (907 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machinePyTorch (1,510 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineU-Net (1,214 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineAutomated machine learning (1,046 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineCaffe (software) (378 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineConference on Neural Information Processing Systems (1,236 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineTheta model (5,025 words) [view diff] exact match in snippet view article find links to article
biology. McKennoch et al. (2008) derived a steepest gradient descent learning rule based on theta neuron dynamics. Their model is based on the assumptionStatistical learning theory (1,709 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineLearning curve (machine learning) (749 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineLocal outlier factor (1,649 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineCompetitive learning (775 words) [view diff] exact match in snippet view article find links to article
maps (Kohonen maps). There are three basic elements to a competitive learning rule: A set of neurons that are all the same except for some randomly distributedEcho state network (1,745 words) [view diff] exact match in snippet view article find links to article
They, ESNs and the newly researched backpropagation decorrelation learning rule for RNNs are more and more summarized under the name Reservoir ComputingOnline machine learning (4,747 words) [view diff] exact match in snippet view article find links to article
Some simple online convex optimisation algorithms are: The simplest learning rule to try is to select (at the current step) the hypothesis that has theSamy Bengio (1,079 words) [view diff] case mismatch in snippet view article find links to article
Computer Science in 1993 with a thesis titled Optimization of a Parametric Learning Rule for Neural Networks from the Université de Montréal. Before that, BengioKernel method (1,670 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineTemporal difference learning (1,565 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineEmpirical risk minimization (1,618 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineOntology learning (1,276 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineDeepDream (1,779 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineProper generalized decomposition (1,469 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineData augmentation (1,838 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineOPTICS algorithm (2,133 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineLogistic model tree (220 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineNeural cryptography (2,224 words) [view diff] exact match in snippet view article find links to article
following learning rules can be used for the synchronization: Hebbian learning rule: w i + = g ( w i + σ i x i Θ ( σ i τ ) Θ ( τ A τ B ) ) {\displaystyleInfomax (533 words) [view diff] exact match in snippet view article find links to article
1016/S0042-6989(97)00121-1. PMC 2882863. PMID 9425547. Linsker R (1997). "A local learning rule that enables information maximization for arbitrary input distributions"Mean shift (1,983 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineFuzzy clustering (2,032 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineOccam learning (1,710 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineActive learning (machine learning) (2,211 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineProbabilistic classification (1,179 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineTransfer learning (1,634 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineTensorFlow (4,060 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineFeature engineering (2,183 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSelf-supervised learning (2,047 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineConditional random field (2,065 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineIndependent component analysis (7,462 words) [view diff] exact match in snippet view article find links to article
PMC 3538438. PMID 23277597. Isomura, Takuya; Toyoizumi, Taro (2016). "A local learning rule for independent component analysis". Scientific Reports. 6: 28073. Bibcode:2016NatSRBCM theory (2,356 words) [view diff] exact match in snippet view article find links to article
decay of all synapses. This model is a modified form of the Hebbian learning rule, m j ˙ = c d j {\displaystyle {\dot {m_{j}}}=cd_{j}} , and requiresBIRCH (2,275 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineWulfram Gerstner (1,523 words) [view diff] exact match in snippet view article find links to article
Kempter, Richard; Van Hemmen, J. Leo; Wagner, Hermann (1996). "A neuronal learning rule for sub-millisecond temporal coding" (PDF). Nature. 383 (6595): 76–78Q-learning (3,835 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineAlmeida–Pineda recurrent backpropagation (204 words) [view diff] exact match in snippet view article find links to article
1103/PhysRevLett.59.2229. PMID 10035458. Almeida, Luis B. (June 1987). A learning rule for asynchronous perceptrons with feedback in a combinatorial environmentBoosting (machine learning) (2,240 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineActivation function (1,960 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineBigDL (57 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRegression analysis (5,235 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineNeuroph (157 words) [view diff] exact match in snippet view article find links to article
layer, neuron connections, weight, transfer function, input function, learning rule etc. Neuroph supports common neural network architectures such as MultilayerLanguage model (2,374 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRectifier (neural networks) (2,990 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineIan Witten (937 words) [view diff] exact match in snippet view article find links to article
learning, inventing the tabular TD(0), the first temporal-difference learning rule for reinforcement learning. Witten was a co-creator of the SequiturPutamen (3,305 words) [view diff] no match in snippet view article find links to article
not these lesions affect rule-based and information-integration task learning. Rule-based tasks are learned via hypothesis-testing dependent on workingSynaptic plasticity (3,613 words) [view diff] exact match in snippet view article find links to article
S2CID 2048100. Cooper SJ (January 2005). "Donald O. Hebb's synapse and learning rule: a history and commentary". Neuroscience and Biobehavioral Reviews.Out-of-bag error (723 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineData mining (4,934 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineBootstrap aggregating (2,430 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineNeural network (machine learning) (17,641 words) [view diff] exact match in snippet view article
Shun'ichi Amari proposed to modify the weights of an Ising model by Hebbian learning rule as a model of associative memory, adding in the component of learningCanonical correlation (3,645 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineWeak supervision (3,038 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGrammar induction (2,166 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineDBSCAN (3,492 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineChemical synapse (4,277 words) [view diff] case mismatch in snippet view article find links to article
Bernard; Kim, Youngsik; Park, Dookun; Perin, Jose Krause (2019). "Nature's Learning Rule". Artificial Intelligence in the Age of Neural Networks and Brain ComputingSpike-timing-dependent plasticity (7,405 words) [view diff] exact match in snippet view article find links to article
neuronal firing. As early as 1973, M. M. Taylor proposed a theoretical learning rule in which synapses would be strengthened if a presynaptic spike reliablyTraining, validation, and test data sets (2,212 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineHierarchical clustering (3,496 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRestricted Boltzmann machine (2,364 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineWord2vec (4,250 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMachine learning (15,573 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMacroeconomic model (2,300 words) [view diff] exact match in snippet view article find links to article
preferences are specified, together with an initial strategy and a learning rule whereby the strategy is adjusted according to its past success. GivenSeinfeld (12,778 words) [view diff] no match in snippet view article find links to article
improve throughout the series was expressed as the "no hugging, no learning" rule. Larry David was adamant from the beginning that he did not want theChatbot (6,604 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineNeural gas (1,807 words) [view diff] exact match in snippet view article find links to article
network model that learns topological relations by using a "Hebb-like learning rule", only, unlike the neural gas, it has no parameters that change overOverfitting (2,843 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineWord embedding (3,154 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGradient descent (5,600 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machinePattern recognition (4,363 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineK-SVD (1,308 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineCosine similarity (3,084 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineAnomaly detection (4,419 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSelf-organizing map (4,068 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGeneralized Hebbian algorithm (1,258 words) [view diff] exact match in snippet view article find links to article
{\displaystyle i} -th output neurons. The generalized Hebbian algorithm learning rule is of the form Δ w i j = η y i ( x j − ∑ k = 1 i w k j y k ) {\displaystyleVapnik–Chervonenkis theory (3,937 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSoftmax function (5,279 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineLabeled data (851 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSwarm intelligence (5,034 words) [view diff] case mismatch in snippet view article find links to article
Myrmecology Promise theory Quorum sensing Population protocol Reinforcement learning Rule 110 Self-organized criticality Spiral optimization algorithm StochasticLong short-term memory (5,814 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineNeural Engineering Object (747 words) [view diff] exact match in snippet view article find links to article
computed, instead of forcing the weights to be set manually, or use a learning rule to configure them from a random start. That being said, these aforementionedGPT-2 (3,264 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineFeature scaling (1,041 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineEnsemble learning (6,685 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineReinforcement learning (8,193 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGPT-3 (4,923 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineErnst Ising (1,185 words) [view diff] exact match in snippet view article find links to article
in 1972 proposed to modify the weights of an Ising model by Hebbian learning rule as a model of associative memory, adding in the component of learningMulti-agent reinforcement learning (3,030 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineDeep belief network (1,280 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRandom forest (6,483 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineLearning rate (1,108 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineDecision tree learning (6,542 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineAttention (machine learning) (3,427 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machinePerceptron (6,297 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineK-means clustering (7,754 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineCurse of dimensionality (4,186 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineTransformer (deep learning architecture) (13,108 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSupport vector machine (9,071 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineBias–variance tradeoff (4,228 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineProper orthogonal decomposition (678 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineAutoencoder (6,214 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineVariational autoencoder (3,967 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRule-based machine learning (536 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineHebbian theory (4,344 words) [view diff] exact match in snippet view article find links to article
Natalia; Dan, Yang (2008). "Spike timing-dependent plasticity: a Hebbian learning rule". Annual Review of Neuroscience. 31: 25–46. doi:10.1146/annurev.neuroDeeplearning4j (1,378 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRandom sample consensus (4,146 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineBackpropagation (7,993 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSparse dictionary learning (3,499 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineCatastrophic interference (4,482 words) [view diff] exact match in snippet view article find links to article
changes (similar to error backpropagation). Kortge (1990) proposed a learning rule for training neural networks, called the 'novelty rule', to help alleviateCluster analysis (9,513 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineNeighbourhood components analysis (1,166 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machinePrincipal component analysis (14,851 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineDeep learning (17,775 words) [view diff] exact match in snippet view article find links to article
R. A.; Jordan, M. I. (15 May 1991). "A more biologically plausible learning rule for neural networks". Proceedings of the National Academy of SciencesExpectation–maximization algorithm (7,512 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineBoltzmann machine (3,676 words) [view diff] exact match in snippet view article find links to article
network is free-running is given by the Boltzmann distribution. This learning rule is biologically plausible because the only information needed to changeFeature (computer vision) (2,935 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSemantic folding (1,641 words) [view diff] no match in snippet view article find links to article
create either rule-based NLP systems or training corpora for model learning. Rule-based and machine learning-based models are fixed on the keyword levelNeuroplasticity (13,307 words) [view diff] exact match in snippet view article find links to article
in 1943, McCulloch and Pitts proposed the artificial neuron, with a learning rule, whereby new synapses are produced when neurons fire simultaneouslyLogic learning machine (621 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineLearning to rank (4,442 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineFactor analysis (10,024 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machinePlatt scaling (831 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineAction model learning (1,131 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineStochastic gradient descent (7,016 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineFeature learning (5,114 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineKnowledge extraction (4,413 words) [view diff] no match in snippet view article find links to article
non-taxonomic relations, instances, axioms NLP, statistical methods, machine learning, rule-based methods OWL deomain-independent English, German, Spanish Text-To-OntoIncremental learning (603 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineConvolutional neural network (15,585 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGradient boosting (4,259 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMeta-learning (computer science) (2,496 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRecursive neural network (914 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineIlana B. Witten (2,686 words) [view diff] exact match in snippet view article find links to article
IB, Knudsen PF, Knudsen EI. PLoS ONE. 2010; 5(4): e10396. A Hebbian learning rule mediates asymmetric plasticity in aligning sensory representations.Association rule learning (6,709 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGraph neural network (4,791 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGenerative adversarial network (13,887 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineQuantum machine learning (9,369 words) [view diff] exact match in snippet view article find links to article
quantum Boltzmann machine has been trained in the D-Wave 2X by using a learning rule analogous to that of classical Boltzmann machines. Quantum annealingHoshen–Kopelman algorithm (1,625 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMlpack (1,438 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineHuman contingency learning (2,561 words) [view diff] exact match in snippet view article find links to article
unconditional stimuli.: This relationship can be expressed under the following learning rule or mathematical equation Δ V n = α β ( λ − Σ V n − 1 ) {\displaystyleKernel perceptron (1,179 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineTypes of artificial neural networks (10,702 words) [view diff] exact match in snippet view article find links to article
in a standard feedforward fashion, and then a backpropagation-like learning rule is applied (not performing gradient descent). The fixed back connectionsBatch normalization (5,892 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineNon-negative matrix factorization (7,783 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineIsing model (13,240 words) [view diff] exact match in snippet view article find links to article
1972), proposed to modify the weights of an Ising model by Hebbian learning rule as a model of associative memory. The same idea was published by (WilliamPredictive mean matching (210 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineTempotron (574 words) [view diff] exact match in snippet view article find links to article
N., & Dan, Y. (2008). Spike timing-dependent plasticity: a Hebbian learning rule. Annu Rev Neurosci, 31, 25-46. Robert Gütig, Haim Sompolinsky (2006):Adversarial machine learning (7,819 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineCoDi (1,210 words) [view diff] exact match in snippet view article find links to article
is based on evolutionary algorithms, has been augmented with a local learning rule via feedback from dendritic spikes by Schwarzer. Artificial brain BiologicalMemristor (13,824 words) [view diff] exact match in snippet view article find links to article
Learning is based on the creation of fuzzy relations inspired from Hebbian learning rule. In 2013 Leon Chua published a tutorial underlining the broad span ofAdaBoost (4,870 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineLoss functions for classification (4,212 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineDouble descent (923 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMulticlass classification (4,573 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineClaudia Clopath (741 words) [view diff] exact match in snippet view article find links to article
on 2017-03-15. Retrieved 2019-10-15. "Brain--inspired disinhihbitory learning rule for continual learning tasks in artificial neural networks". UKRI. "GoogleVanishing gradient problem (3,705 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineJacek M. Zurada (2,001 words) [view diff] exact match in snippet view article find links to article
learning, decomposition methods for salient feature extraction, and lambda learning rule for neural networks. His work has advanced fundamental understandingLeakage (machine learning) (1,027 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineThe Evolution of Cooperation (4,841 words) [view diff] exact match in snippet view article find links to article
with punishment, are chosen in alignment with the agent's prevailing learning rule. Simulations of the model under conditions approximating those experiencedError tolerance (PAC learning) (1,904 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSpatial embedding (1,961 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMathematical models of social learning (966 words) [view diff] exact match in snippet view article find links to article
, that they have a reliable model of the world and that the social learning rule of each agent is common knowledge among all members of the communityList of datasets for machine-learning research (15,006 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineIla Fiete (1,855 words) [view diff] exact match in snippet view article find links to article
neurophysiological data of songbirds and found that the trial-and-error based learning rule was fast enough to explain learning in songbirds. When Fiete startedNeural architecture search (2,980 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSample complexity (2,202 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineModel-free (reinforcement learning) (614 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMathematics of artificial neural networks (1,790 words) [view diff] exact match in snippet view article find links to article
\textstyle Y} . Sometimes models are intimately associated with a particular learning rule. A common use of the phrase "ANN model" is really the definition ofMultimodal learning (2,212 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineExtreme learning machine (3,644 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineFusion adaptive resonance theory (2,200 words) [view diff] exact match in snippet view article find links to article
c k {\displaystyle {\vec {w}}_{J}^{ck}} is modified according to a learning rule which moves it towards the input pattern. When an uncommitted node isMultiple instance learning (5,479 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineError-driven learning (1,933 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineCount sketch (1,466 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineSentence embedding (973 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineVALL-E (141 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineTensor sketch (4,517 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineTsetlin machine (2,921 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineVicuna LLM (292 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGPTeens (217 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineAndrzej Cichocki (1,666 words) [view diff] exact match in snippet view article find links to article
Shun-ichi (1995). "Multi-layer neural networks with a local adaptive learning rule for blind separation of source signals" (PDF). Proceedings of the 1995IBM Granite (499 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMultiple kernel learning (2,856 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineProximal policy optimization (2,504 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineWaluigi effect (627 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineHistory of artificial neural networks (8,625 words) [view diff] exact match in snippet view article find links to article
in 1972 proposed to modify the weights of an Ising model by Hebbian learning rule as a model of associative memory, adding in the component of learningPerceptrons (book) (5,184 words) [view diff] exact match in snippet view article
could perform credit assignment any better than Rosenblatt's perceptron learning rule, and perceptrons cannot represent the knowledge required for solvingAlbumentations (429 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMixture of experts (5,651 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineAI/ML Development Platform (558 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMindSpore (478 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineWasserstein GAN (2,884 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineRandom flip-flop (1,149 words) [view diff] case mismatch in snippet view article find links to article
Cesare; Choe, Yoonsuck; Morabito, Francesco Carlo (eds.), "Nature's Learning Rule", Artificial Intelligence in the Age of Neural Networks and Brain ComputingIBM Watsonx (634 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMamba (deep learning architecture) (1,159 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineCurriculum learning (1,367 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMechanistic interpretability (1,195 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGPT-1 (1,064 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineDiffusion model (14,123 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineConvolutional layer (1,424 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineMultilayer perceptron (1,932 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineVector database (1,633 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineFlow-based generative model (8,747 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineWeight initialization (2,916 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGPT-4 (6,200 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineGenerative pre-trained transformer (5,278 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineLarge language model (11,789 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineNormalization (machine learning) (5,361 words) [view diff] case mismatch in snippet view article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineReinforcement learning from human feedback (8,617 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machineList of datasets in computer vision and image processing (7,858 words) [view diff] case mismatch in snippet view article find links to article
Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic engineering Quantum machine