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Monday Webinar - Generalized Tensor Decomposition. Utility for Data Analysis
Interpretable Nonlinear Dynamic Modeling of Neural Trajectories [NIPS 2016 spotlight]
Tensor Decomposition based Adaptive Model Reduction
DISCO Nets : DISsimilarity COefficient Networks (NIPS 2016)
Non-negative Matrix and Tensor Factorization for Customer Behavior Analysis
RecSys 2016 - Matrix and Tensor Decomposition in Recommender Systems
Tensor Decompositions: Uniqueness and Smoothed Analysis
Tensor Decompositions for Learning Latent Variable Models I
Spotlight Talk: Convolutional Dictionary Learning through Tensor Factorization
Discovery of Latent Factors in High-dimensional Data via Tensor Decomposition
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Last Updated: October 21, 2026
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JMM 2018: Tamara G. Kolda, Sandia National Laboratories, gives the SIAM Invited Address on " Recording during the thematic meeting: «Nexus of Information and Computation Theories » theJanuary 27, This is a 3-min spotlight video to be featured on the This video demonstrates an adaptive model reduction approach based on DISCO Nets : DISsimilarity COefficient Networks We present a system to analyze consumer be- havior and cluster the customers accordingly. It is based on matrix and This tutorial offers a rich blend of theory and practice regarding dimensionality reduction methods, to address the information ... Moses Charikar, Princeton University Semidefinite Optimization, Approximation and Applications ... Daniel Hsu, Columbia University simons.berkeley.edu/talks/daniel-hsu-01-27-2017-1 Foundations of Machine Learning ... Furong Huang, UC Irvine Representation Learning simons.berkeley.edu/talks/furong-huang-2017-03-29. Latent or hidden variable models have applications in almost every domain, e.g., social network analysis, natural language ...
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