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Longer titles found: Nonlinear dimensionality reduction (view), Multifactor dimensionality reduction (view)

searching for Dimensionality reduction 70 found (387 total)

alternate case: dimensionality reduction

Multilinear subspace learning (1,550 words) [view diff] exact match in snippet view article find links to article

causal factor of data formation and performing dimensionality reduction. The Dimensionality reduction can be performed on a data tensor that contains

Semidefinite embedding (1,572 words) [view diff] exact match in snippet view article find links to article

science that uses semidefinite programming to perform non-linear dimensionality reduction of high-dimensional vectorial input data. It is motivated by the

Sliced inverse regression (1,511 words) [view diff] exact match in snippet view article find links to article

Sliced inverse regression (SIR) is a tool for dimensionality reduction in the field of multivariate statistics. In statistics, regression analysis is a

Chiara Sabatti (304 words) [view diff] case mismatch in snippet view article find links to article

her Ph.D. in 1998. Her dissertation, Group Transformations and Dimensionality Reduction in Transition Rules for MCMC, was supervised by Jun S. Liu. After

Terry R. Payne (390 words) [view diff] case mismatch in snippet view article find links to article

1994, followed by his PhD from the same institution for his work "Dimensionality Reduction and Representation for Nearest Neighbour Learning". Between 1998-2002

Geometric data analysis (196 words) [view diff] case mismatch in snippet view article find links to article

Kirby (2001). Geometric Data Analysis: An Empirical Approach to Dimensionality Reduction and the Study of Patterns. Wiley. ISBN 978-0-4712-3929-1. Brigitte

Graduated optimization (783 words) [view diff] exact match in snippet view article find links to article

graduated optimization to seek a manifold embedding for non-linear dimensionality reduction. It gradually scales variance out of extra dimensions within a

Fakhreddine Karray (1,954 words) [view diff] case mismatch in snippet view article find links to article

analysis and machine intelligence and is the co-author of Elements of Dimensionality Reduction and Manifold Learning and Soft Computing and Intelligent Systems

Clustering high-dimensional data (2,284 words) [view diff] exact match in snippet view article find links to article

, & Kaski, S.: Information retrieval perspective to nonlinear dimensionality reduction for data visualization, The Journal of Machine Learning Research

Data Science and Predictive Analytics (686 words) [view diff] case mismatch in snippet view article find links to article

Data in R Data Visualization Linear Algebra & Matrix Computing Dimensionality Reduction Lazy Learning: Classification Using Nearest Neighbors Probabilistic

Contact mechanics (12,049 words) [view diff] exact match in snippet view article find links to article

hemispherical cup). Some contact problems can be solved with the method of dimensionality reduction (MDR). In this method, the initial three-dimensional system is

Data Analytics Library (637 words) [view diff] exact match in snippet view article find links to article

Principal Component Analysis (PCA): the most popular algorithm for dimensionality reduction. Association rules mining: Detecting co-occurrence patterns. Commonly

Shen Qiang (engineer) (430 words) [view diff] exact match in snippet view article

co-authors studied methodologies and approaches of Semantics-preserving dimensionality reduction techniques. In 2009, he was the recipient of the Computational

Phoenix network coordinates (575 words) [view diff] exact match in snippet view article find links to article

This matrix factorization is essentially a problem of linear dimensionality reduction and Phoenix tries to solve it in a distributed way. Different from

Ontology for Biomedical Investigations (910 words) [view diff] exact match in snippet view article find links to article

and data analysis) – for example principal components analysis dimensionality reduction, mean calculation Less 'concrete' aspects such as the role a given

Isometry (2,425 words) [view diff] exact match in snippet view article find links to article

University. p. 125. Roweis, S.T.; Saul, L.K. (2000). "Nonlinear dimensionality reduction by locally linear embedding". Science. 290 (5500): 2323–2326. Bibcode:2000Sci

Shogun (toolbox) (468 words) [view diff] exact match in snippet view article

Shogun supports the following algorithms: Support vector machines Dimensionality reduction algorithms, such as PCA, Kernel PCA, Locally Linear Embedding,

Computational genomics (1,992 words) [view diff] no match in snippet view article find links to article

important parts of these tools. These processes can consist of dimensionality -reduction techniques, such as Minhash, and clusterization algorithms such

Holographic associative memory (892 words) [view diff] exact match in snippet view article find links to article

neuroscience Self-organizing map – Machine learning technique useful for dimensionality reduction Sparse distributed memory – Mathematical model of memory Khan,

Knowledge graph (2,342 words) [view diff] exact match in snippet view article find links to article

repository with multiple applications Knowledge graph embedding – Dimensionality reduction of graph-based semantic data objects [machine learning task] Logical

Andrzej Cichocki (1,669 words) [view diff] case mismatch in snippet view article find links to article

A. H., Zhao, Q., & Mandic, D. P. (2016). Tensor Networks for Dimensionality Reduction and Large-Scale Optimization: Part 1 Low-Rank Tensor Decompositions

Metabolic gene cluster (1,175 words) [view diff] no match in snippet view article find links to article

important parts of these tools. These processes can consist of dimensionality -reduction techniques, such as Minhash, and clusterization algorithms such

MANIC (cognitive architecture) (569 words) [view diff] case mismatch in snippet view article

conscious beings. Gashler, M. and Martinez, T., Temporal Nonlinear Dimensionality Reduction, In Proceedings of the International Joint Conference on Neural

Catherine Havasi (747 words) [view diff] case mismatch in snippet view article find links to article

Henry Lieberman.'Digital Intuition: Applying Common Sense Using Dimensionality Reduction. IEEE Journal of Intelligent Systems, 24(4) July 2009. (cited 97

Data stream clustering (2,047 words) [view diff] exact match in snippet view article find links to article

traditional clustering techniques ineffective. Techniques such as dimensionality reduction, feature selection, or subspace clustering are often used in conjunction

VALCRI (807 words) [view diff] case mismatch in snippet view article find links to article

Sacha, Dominik (February 2017). "Applying Visual Interactive Dimensionality Reduction to Criminal Intelligence Analysis" (PDF). Duquenoy, P. (2018).

Code stylometry (1,177 words) [view diff] exact match in snippet view article find links to article

pseudocode through decompilation to obtain abstract syntax trees. Dimensionality reduction - The most relevant and useful features for author identification

Piranha (software) (592 words) [view diff] case mismatch in snippet view article

Proceedings of the IEEE Swarm Intelligence Symposium, St. Louis, Mo. Dimensionality Reduction for High Dimensional Particle Swarm Clustering. Yasin, Rutrell

Wavelet transform (3,836 words) [view diff] case mismatch in snippet view article find links to article

phycom.2009.07.001. Sheybani, E.; Javidi, G. (December 2009). "Dimensionality Reduction and Noise Removal in Wireless Sensor Network Datasets". 2009 Second

ICPRAM (2,059 words) [view diff] case mismatch in snippet view article find links to article

Gisbrecht and Alexander Schulz. "Applications of Discriminative Dimensionality Reduction" Best Student Paper: Cristina Garcia-Cardona, Arjuna Flenner and

Cecilia Clementi (699 words) [view diff] exact match in snippet view article find links to article

free-energy landscapes of protein-folding reactions by nonlinear dimensionality reduction". Proceedings of the National Academy of Sciences. 103 (26): 9885–9890

Dana Pe'er (2,592 words) [view diff] exact match in snippet view article find links to article

cells at a time. They introduced the application of non-linear dimensionality reduction by t-distributed stochastic neighbor embedding (t-SNE) to visualize

Izhar Bar-Gad (539 words) [view diff] exact match in snippet view article find links to article

dissertation was written on the subject of "Reinforcement driven dimensionality reduction as a model for information processing in the basal ganglia". Born

Holonomic brain theory (3,470 words) [view diff] exact match in snippet view article find links to article

mechanics Self-organizing map – Machine learning technique useful for dimensionality reduction Sparse distributed memory – Mathematical model of memory Visual

Opinion Space (661 words) [view diff] case mismatch in snippet view article find links to article

Sanjay Krishnan and Ken Goldberg (June 2013). "Distributed Spectral Dimensionality Reduction for Visualizing Textual Data" (PDF). International Conference on

Tf–idf (2,975 words) [view diff] exact match in snippet view article find links to article

text mining (TM) specifically i) indexing, ii) retrieval, iii) dimensionality reduction, iv) clustering, v) classification. The indexing step offers the

Ludwig Föppl (2,149 words) [view diff] case mismatch in snippet view article find links to article

Class With Swords - 12 September 1916 Bearing capacity Method of Dimensionality Reduction Triakis truncated tetrahedron Samuels, Martin (3 June 2016). "Ludwig

Speech recognition (13,147 words) [view diff] exact match in snippet view article find links to article

neural networks as a pre-processing, feature transformation or dimensionality reduction, step prior to HMM based recognition. However, more recently, LSTM

Locality-sensitive hashing (4,024 words) [view diff] exact match in snippet view article find links to article

geocoding invented in 2008 Multilinear subspace learning – Approach to dimensionality reduction Principal component analysis – Method of data analysis Random indexing

Multidimensional network (6,972 words) [view diff] exact match in snippet view article find links to article

simplify the structure of such systems by employing some kind of dimensionality reduction. A popular method is based on the calculation of the quantum Jensen-Shannon

Sankar Kumar Pal (2,556 words) [view diff] exact match in snippet view article find links to article

other highly cited original research include: i) Unsupervised dimensionality reduction algorithm (in early 2000s) producing maximally independent features

Peter Capak (1,519 words) [view diff] exact match in snippet view article find links to article

Daniel; Shahidi, Abtin (2019). "Bringing manifold learning and dimensionality reduction to SED fitters". The Astrophysical Journal. 881 (1): L14. arXiv:1905

Cross-validation (statistics) (5,781 words) [view diff] exact match in snippet view article

training set must be performed. Performing mean-centering, rescaling, dimensionality reduction, outlier removal or any other data-dependent preprocessing using

Lighting (7,994 words) [view diff] exact match in snippet view article find links to article

Kent, Michael; Schiavon, Stefano; Jakubiec, Alstan (2020). "A dimensionality reduction method to select the most representative daylight illuminance distributions"

Isolation forest (4,555 words) [view diff] exact match in snippet view article find links to article

Smaller subsample reduces cost. Larger subsample increases accuracy. Dimensionality reduction can optimize subsample size. Smaller subsample for efficiency.

K-nearest neighbors algorithm (4,333 words) [view diff] exact match in snippet view article find links to article

S2CID 8522279 Bingham, Ella; Mannila, Heikki (2001). "Random projection in dimensionality reduction". Proceedings of the seventh ACM SIGKDD international conference

Fault detection and isolation (3,228 words) [view diff] exact match in snippet view article find links to article

learning models extract a few feature values from signals, causing a dimensionality reduction from the original signal. By using Convolutional neural networks

Hanoch Senderowitz (1,507 words) [view diff] case mismatch in snippet view article find links to article

Hanoch (2018). "Visualization of Solar Cell Library Space by Dimensionality Reduction Methods". Journal of Chemical Information and Modeling. 58 (12):

Anastasios Venetsanopoulos (3,111 words) [view diff] case mismatch in snippet view article find links to article

Applications", "WLAN Positioning Systems", "Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data". He was supported by grants from the

Kwan-Liu Ma (1,234 words) [view diff] case mismatch in snippet view article find links to article

Takanori Fujiwara, Oh-Hyun Kwon, Kwan-Liu Ma: Supporting Analysis of Dimensionality Reduction Results with Contrastive Learning. IEEE Trans. Vis. Comput. Graph

Multivariate t-distribution (5,719 words) [view diff] exact match in snippet view article find links to article

^{m\times p},m<p} , of rank m {\displaystyle m} the result is dimensionality reduction. Here, Jacobian | Θ | {\displaystyle \left|\Theta \right|} is seemingly

Interleaving distance (997 words) [view diff] case mismatch in snippet view article find links to article

Nelson, Bradley J.; Luo, Yuan (2022-01-31). "Topology-Preserving Dimensionality Reduction via Interleaving Optimization". arXiv:2201.13012 [cs.LG]. "Interleaving

Monte Carlo methods in finance (4,172 words) [view diff] exact match in snippet view article find links to article

analysts may apply Principal component analysis, where through dimensionality reduction, a limited set of factors may be simulated instead of each of the

Daylighting (architecture) (5,791 words) [view diff] exact match in snippet view article

Kent, Michael; Schiavon, Stefano; Jakubiec, Alstan (2020). "A dimensionality reduction method to select the most representative daylight illuminance distributions"

Carsen Stringer (1,661 words) [view diff] exact match in snippet view article find links to article

rodent visual cortex and she used a variety of machine learning and dimensionality reduction techniques to explore the network level mechanisms that give rise

Latent semantic analysis (7,613 words) [view diff] case mismatch in snippet view article find links to article

White Paper, Fios, Inc. Karypis, G., Han, E., Fast Supervised Dimensionality Reduction Algorithm with Applications to Document Categorization and Retrieval

Kernel Fisher discriminant analysis (3,659 words) [view diff] case mismatch in snippet view article find links to article

Discriminant Analysis in C# - C# code to perform KFD. Matlab Toolbox for Dimensionality Reduction - Includes a method for performing KFD. Handwriting Recognition

César Hidalgo (2,325 words) [view diff] exact match in snippet view article find links to article

likely to enter an exit, and the economic complexity index, a dimensionality reduction based formula that can be used to explain differences in economic

List of women in statistics (8,599 words) [view diff] exact match in snippet view article find links to article

Chiaromonte, Italian statistician, expert on statistical genetics and dimensionality reduction Marcia Ciol, Brazilian-American expert on comorbidity Constance

Ultraconserved element (4,445 words) [view diff] case mismatch in snippet view article find links to article

associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR)". BioData Mining. 8 (1): 41. doi:10.1186/s13040-015-0074-0

Cluster II (spacecraft) (12,933 words) [view diff] case mismatch in snippet view article

1029/2020JA028084. Bakrania, M.R.; Rae, I.J.; Walsh, A.P. (2020). "Using Dimensionality Reduction and Clustering Techniques to Classify Space Plasma Regimes". Front

Primate basal ganglia (7,533 words) [view diff] no match in snippet view article find links to article

Bar-Gad, I, Morris, G., Bergman, H. (2003) Information processing, dimensionality, reduction and reinforcement in the basal ganglia. Progr. Neurobiol. 71:

Axel Timmermann (7,240 words) [view diff] exact match in snippet view article find links to article

Quaternary Science Reviews 23 (20), 2219-2230, 2004 Nonlinear dimensionality reduction in climate data, AJ Gamez, CS Zhou, A Timmermann, J Kurths, Nonlinear

Coarse-grained modeling (2,377 words) [view diff] case mismatch in snippet view article find links to article

PMID 33466014. S2CID 231652939. Hummer G, Szabo A (July 2015). "Optimal Dimensionality Reduction of Multistate Kinetic and Markov-State Models". The Journal of

Knowledge graph embedding (5,948 words) [view diff] exact match in snippet view article find links to article

Dimensionality reduction of graph-based semantic data objects [machine learning task]

Patch-sequencing (5,261 words) [view diff] exact match in snippet view article find links to article

alone. Correlation based methods are sufficient for this step. Dimensionality reduction methods such as T-distributed stochastic neighbor embedding or

List of women in mathematics (23,272 words) [view diff] exact match in snippet view article find links to article

Forzani, Argentine applied mathematician and statistician, expert in dimensionality reduction Phyllis Fox (1923–2017), American mathematician and computer scientist

List of RNA-Seq bioinformatics tools (20,393 words) [view diff] exact match in snippet view article find links to article

and noise reduction for single cell RNA-seq experiments. ZIFA Dimensionality reduction for zero-inflated single-cell gene expression analysis. BPSC An

EPIC-Seq (6,409 words) [view diff] exact match in snippet view article find links to article

ctDNA reads. It also checks the histone modifications and applies dimensionality reduction on the found sites to identify putative promoter, enhancer, and

Open-source artificial intelligence (7,003 words) [view diff] exact match in snippet view article find links to article

accessible functions for classification, regression, clustering, and dimensionality reduction. This library simplifies the ML pipeline from data preprocessing