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alternate case: learning rule

Memtransistor (349 words) [view diff] exact match in snippet view article find links to article

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 is
BCPNN (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 intrinsic
Unsupervised 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 Inference
Phi Kappa Phi (2,398 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 words
Delta 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-layer
Win–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. Outcomes
Synaptic weight (525 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 in
Rishikesh 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 2934916
International Conference on Machine Learning (386 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
Parallel processing (psychology) (2,083 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 is
Self-play (501 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
Semantic 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 level
International Conference on Learning Representations (272 words) [view diff] case mismatch in snippet view article find links to article
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Amos 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, machine
Computational learning theory (865 words) [view diff] case mismatch in snippet view article find links to article
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Winner-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 applied
CURE algorithm (788 words) [view diff] case mismatch in snippet view article find links to article
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Feedforward 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 layer
Differentiable programming (1,021 words) [view diff] case mismatch in snippet view article find links to article
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Relevance 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 machine
Gated recurrent unit (1,290 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
Structured prediction (773 words) [view diff] case mismatch in snippet view article find links to article
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Graphical model (1,278 words) [view diff] case mismatch in snippet view article find links to article
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WaveNet (1,699 words) [view diff] case mismatch in snippet view article find links to article
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Storage (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 allow
State–action–reward–state–action (716 words) [view diff] case mismatch in snippet view article find links to article
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Rule-based system (1,183 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). Intelligent
Human-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 machine
Feature (machine learning) (1,027 words) [view diff] case mismatch in snippet view article
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Automated machine learning (1,034 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
U-Net (1,285 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
Probably approximately correct learning (907 words) [view diff] case mismatch in snippet view article find links to article
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Theta 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 assumption
Conference on Neural Information Processing Systems (1,236 words) [view diff] case mismatch in snippet view article find links to article
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Learning curve (machine learning) (749 words) [view diff] case mismatch in snippet view article
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Competitive 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 distributed
PyTorch (1,540 words) [view diff] case mismatch in snippet view article find links to article
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Local outlier factor (1,649 words) [view diff] case mismatch in snippet view article find links to article
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Echo state network (1,748 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 Computing
Caffe (software) (378 words) [view diff] case mismatch in snippet view article
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Online 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 the
Statistical learning theory (1,712 words) [view diff] case mismatch in snippet view article find links to article
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Kernel method (1,670 words) [view diff] case mismatch in snippet view article find links to article
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Samy 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, Bengio
Empirical risk minimization (1,618 words) [view diff] case mismatch in snippet view article find links to article
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Temporal difference learning (1,565 words) [view diff] case mismatch in snippet view article find links to article
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Ontology learning (1,276 words) [view diff] case mismatch in snippet view article find links to article
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Proper generalized decomposition (1,469 words) [view diff] case mismatch in snippet view article find links to article
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DeepDream (1,779 words) [view diff] case mismatch in snippet view article find links to article
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Data augmentation (1,838 words) [view diff] case mismatch in snippet view article find links to article
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Neural 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 ) ) {\displaystyle
Logistic model tree (220 words) [view diff] case mismatch in snippet view article find links to article
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OPTICS algorithm (2,133 words) [view diff] case mismatch in snippet view article find links to article
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Infomax (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
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Fuzzy clustering (2,039 words) [view diff] case mismatch in snippet view article find links to article
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Occam 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 machine
Transfer learning (1,651 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 machine
Active 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 machine
TensorFlow (4,064 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 machine
Probabilistic classification (1,179 words) [view diff] case mismatch in snippet view article find links to article
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Spike-timing-dependent plasticity (5,522 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 reliably
Wulfram 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): 76–78
BCM 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 requires
Conditional random field (2,065 words) [view diff] case mismatch in snippet view article find links to article
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Independent 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:2016NatSR
BIRCH (2,275 words) [view diff] case mismatch in snippet view article find links to article
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Feature engineering (2,184 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
Activation function (1,963 words) [view diff] case mismatch in snippet view article find links to article
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Regression analysis (5,235 words) [view diff] case mismatch in snippet view article find links to article
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Almeida–Pineda recurrent backpropagation (207 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 environment
Self-supervised learning (2,047 words) [view diff] case mismatch in snippet view article find links to article
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Rectifier (neural networks) (3,056 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 machine
BigDL (60 words) [view diff] case mismatch in snippet view article find links to article
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Boosting (machine learning) (2,178 words) [view diff] case mismatch in snippet view article
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Neuroph (160 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 Multilayer
Ian 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 Sequitur
Language model (2,424 words) [view diff] case mismatch in snippet view article find links to article
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Synaptic 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
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Putamen (3,307 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 working
Data mining (4,934 words) [view diff] case mismatch in snippet view article find links to article
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Bootstrap aggregating (2,430 words) [view diff] case mismatch in snippet view article find links to article
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Chatbot (5,529 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
Canonical correlation (3,645 words) [view diff] case mismatch in snippet view article find links to article
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Weak 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 machine
Q-learning (3,856 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 machine
DBSCAN (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 machine
Neural network (machine learning) (17,613 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 learning
Hierarchical clustering (3,067 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
Neuromorphic computing (4,912 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
Restricted 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 machine
Training, 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 machine
Machine learning (15,562 words) [view diff] case mismatch in snippet view article find links to article
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Seinfeld (12,773 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 the
Neural 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 over
Overfitting (2,848 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
Grammar induction (2,166 words) [view diff] case mismatch in snippet view article find links to article
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Chemical 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 Computing
Cosine similarity (3,084 words) [view diff] case mismatch in snippet view article find links to article
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Macroeconomic 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. Given
Word2vec (4,242 words) [view diff] case mismatch in snippet view article find links to article
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K-SVD (1,308 words) [view diff] case mismatch in snippet view article find links to article
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Anomaly detection (4,426 words) [view diff] case mismatch in snippet view article find links to article
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Word embedding (3,154 words) [view diff] case mismatch in snippet view article find links to article
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Generalized Hebbian algorithm (1,268 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 ) {\displaystyle
Pattern recognition (4,350 words) [view diff] case mismatch in snippet view article find links to article
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Gradient descent (5,600 words) [view diff] case mismatch in snippet view article find links to article
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Neural 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 aforementioned
Softmax function (5,279 words) [view diff] case mismatch in snippet view article find links to article
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Long short-term memory (5,822 words) [view diff] case mismatch in snippet view article find links to article
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Vapnik–Chervonenkis theory (3,956 words) [view diff] case mismatch in snippet view article find links to article
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Swarm 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 Stochastic
Feature scaling (1,041 words) [view diff] case mismatch in snippet view article find links to article
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Self-organizing map (4,068 words) [view diff] case mismatch in snippet view article find links to article
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GPT-3 (4,897 words) [view diff] case mismatch in snippet view article find links to article
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Reinforcement learning (8,200 words) [view diff] case mismatch in snippet view article find links to article
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Labeled data (851 words) [view diff] case mismatch in snippet view article find links to article
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GPT-2 (3,269 words) [view diff] case mismatch in snippet view article find links to article
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Deep belief network (1,280 words) [view diff] case mismatch in snippet view article find links to article
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Ernst 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 learning
Multi-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 machine
Support 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 machine
Random forest (6,531 words) [view diff] case mismatch in snippet view article find links to article
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Spiking neural network (3,747 words) [view diff] case mismatch in snippet view article find links to article
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K-means clustering (7,770 words) [view diff] case mismatch in snippet view article find links to article
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Perceptron (6,297 words) [view diff] case mismatch in snippet view article find links to article
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Transformer (deep learning architecture) (13,107 words) [view diff] case mismatch in snippet view article
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Curse of dimensionality (4,186 words) [view diff] case mismatch in snippet view article find links to article
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Bias–variance tradeoff (4,228 words) [view diff] case mismatch in snippet view article find links to article
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Decision tree learning (6,542 words) [view diff] case mismatch in snippet view article find links to article
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Proper orthogonal decomposition (678 words) [view diff] case mismatch in snippet view article find links to article
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Rule-based machine learning (536 words) [view diff] case mismatch in snippet view article find links to article
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Variational 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 machine
Hebbian theory (4,395 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.neuro
Random 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 machine
Deeplearning4j (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 machine
Sparse 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 machine
Backpropagation (7,843 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 machine
Learning 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 machine
Catastrophic interference (4,494 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 alleviate
Cluster analysis (9,510 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 machine
Autoencoder (6,540 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
Neighbourhood 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 machine
Principal 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 machine
Boltzmann 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 change
Expectation–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 machine
Ensemble learning (6,692 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
Attention (machine learning) (3,641 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 machine
Feature (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 machine
Deep learning (17,994 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 Sciences
Logic 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 machine
Neuroplasticity (13,394 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 simultaneously
Knowledge extraction (4,445 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-Onto
Semantic 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 level
Learning 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 machine
Platt 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 machine
Incremental 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 machine
Stochastic gradient descent (7,031 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
Recursive neural network (911 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
Factor analysis (10,029 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
Feature 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 machine
Gradient 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 machine
Action 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 machine
Ilana 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.
Meta-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 machine
Graph neural network (4,802 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
Quantum machine learning (8,984 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 annealing
Convolutional 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 machine
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 machine
Hoshen–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 machine
Mlpack (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 machine
Human 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 ) {\displaystyle
Kernel 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 machine
Batch 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 machine
Predictive 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 machine
Ising 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 (William
Tempotron (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):
Types of artificial neural networks (10,769 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 connections
Non-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 machine
Generative adversarial network (13,885 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
AdaBoost (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 machine
Loss 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 machine
CoDi (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 Biological
Adversarial machine learning (7,938 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
Memristor (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 of
Claudia 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. "Google
Double 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 machine
Multiclass classification (4,571 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
Vanishing gradient problem (3,711 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
Jacek 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 understanding
Leakage (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 machine
The 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 experienced
Spatial 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 machine
Mathematical 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 community
List of datasets for machine-learning research (15,010 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
Error 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 machine
Ila 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 started
Neural 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 machine
Sample 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 machine
Multimodal 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 machine
Extreme 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 machine
Fusion 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 is
Error-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 machine
Multiple 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 machine
Count 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 machine
Mathematics of neural networks in machine learning (1,793 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 of
Model-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 machine
Sentence 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 machine
VALL-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 machine
Tensor 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 machine
Vicuna LLM (295 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
Tsetlin 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 machine
Andrzej Cichocki (1,670 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 1995
IBM 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 machine
Proximal 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 machine
Multiple 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 machine
History 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 learning
Perceptrons (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 solving
Mixture of experts (5,634 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 machine
Albumentations (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 machine
Waluigi effect (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 machine
MindSpore (532 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
IBM Watsonx (712 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
Wasserstein 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 machine
Lawrence Udeigwe (883 words) [view diff] case mismatch in snippet view article find links to article
Munro, G. Bard Ermentrout. "Emergent Dynamical Properties of the BCM Learning Rule." Journal of Mathematical Neuroscience. Vol 7:2, (2017), DOI: 10
AI/ML Development Platform (566 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
Random 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 Computing
Mamba (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 machine
Curriculum learning (1,389 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
GPT-1 (1,069 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
Convolutional 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 machine
Diffusion 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 machine
Multilayer 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 machine
Vector database (1,685 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 machine
Neural radiance field (2,616 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
Flow-based generative model (9,669 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
Neural field (2,336 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
Weight initialization (2,919 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
Topological deep learning (3,296 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
Generative pre-trained transformer (5,276 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 machine
GPT-4 (6,043 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
Mechanistic interpretability (4,965 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
Reinforcement 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 machine
Normalization (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 machine
Large language model (14,141 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 machine
List 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