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Dimensionality reduction
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51	UNIVERSITY OF CALIFORNIA RIVERSIDE Dimensionality Reduction Algorithms With Applications to Collaborative Data and Images A Dissertation submitted in partial satisfaction Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:42 Collaboration Recommender systems Social information processing Collaborative filtering Collaborative software Collective intelligence Algorithm
52	Journal of Machine Learning Research3163 Submitted 6/13; Revised 8/13; PublishedDivvy: Fast and Intuitive Exploratory Data Analysis Joshua M. Lewis Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Multivariate statistics Machine learning Dimension reduction Free statistical software Cluster analysis Data mining Nonlinear dimensionality reduction Isomap Dimensionality reduction Orange T-distributed stochastic neighbor embedding Ayasdi
53	CS168: The Modern Algorithmic Toolbox Lecture #4: Dimensionality Reduction Tim Roughgarden & Gregory Valiant April 8, Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2016-06-04 09:49:43 Machine learning Random projection MinHash Nearest neighbor search K-nearest neighbors algorithm Dimensionality reduction Normal distribution Jaccard index Curse of dimensionality Standard deviation Nonlinear dimensionality reduction
54	Non-linear Metric Learning Dor Kedem, Stephen Tyree, Kilian Q. Weinberger Dept. of Comp. Sci. & Engi. Washington U. St. Louis, MO 63130 Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:00:25 Machine learning Mathematical optimization Search algorithms Multivariate statistics Data mining K-nearest neighbors algorithm Color histogram Pattern recognition Statistical classification Nearest neighbor search Least squares Dimensionality reduction
55	Dimensionality Reduction by Learning an Invariant Mapping Raia Hadsell, Sumit Chopra, Yann LeCun The Courant Institute of Mathematical Sciences New York University, 719 Broadway, New York, NY 1003, USA. http://www.cs.nyu Add to Reading List Source URL: yann.lecun.com Language: English - Date: 2006-02-28 22:05:16 Multivariate statistics Machine learning Dimension reduction Dimension Nonlinear dimensionality reduction Computational statistics Dimensionality reduction Manifold K-nearest neighbors algorithm Isomap Multidimensional scaling Embedding
56	Manifold learning algorithms aim to recover the underlying lowdimensional parametrization of the data using either local or global features. It is however widely recognized that the low dimensional parametrizations will Add to Reading List Source URL: mmds-data.org Language: English - Date: 2016-06-23 15:50:48 Machine learning Cybernetics Learning Manifold Dimension reduction Multivariate statistics Nonlinear dimensionality reduction
57	Statistical Inference, Learning and Models in Big Data Franke, Beate; Plante, Jean–François; Roscher, Ribana; Lee, Annie; Smyth, Cathal; Hatefi, Armin; Chen, Fuqi; Gil, Einat; Schwing, Alexander; Selvitella, Aless Add to Reading List Source URL: www.ipb.uni-bonn.de Language: English - Date: 2016-04-29 09:00:54 Machine learning Data management Multivariate statistics Big data Technology forecasting Transaction processing Feature learning Nonlinear dimensionality reduction
58	Journal of Machine Learning Research450 Submitted 11/07; Revised 11/09; Published 1/10 Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting Add to Reading List Source URL: www.cs.stevens.edu Language: English - Date: 2010-02-04 17:27:11 Multivariate statistics Dimension reduction Computational statistics Machine learning Isomap Dimensionality reduction Nonlinear dimensionality reduction Semidefinite embedding Principal component analysis Tensor Manifold Multidimensional scaling
59	Interacting with Massive Behavioral Data Shih-Chieh Su Qualcomm IncMorehouse Drive San Diego, CAUSA Add to Reading List Source URL: poloclub.gatech.edu Language: English - Date: 2016-07-22 15:05:22 Multivariate statistics Multidimensional scaling Dimensionality reduction Isomap T-distributed stochastic neighbor embedding Principal component analysis Algorithm Data visualization Nonlinear dimensionality reduction
60	Using Pre-Trained Models for Fine-Grained Image Classification in Fashion Field Anna Iliukovich-Strakovskaia Alexey Dral Add to Reading List Source URL: kddfashion2016.mybluemix.net Language: English - Date: 2016-08-14 10:56:50 Machine learning Deep learning Convolutional neural network Pattern recognition Artificial neural network Computer vision Boosting Supervised learning Dimensionality reduction ImageNet Statistical classification Cross-validation

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