
Inderjit S. Dhillon's Talks
Selected Talks
 MultiOutput Prediction: Theory and Challenges, Keynote Talk, PAKDD, Singapore, 2020
[pdf]
[video]
 Stabilizing Gradients for Deep Neural Networks, Keynote Talk, Harvard Data Science Initiative Conference (HDSI), 2018
[pdf]
[video]
 MultiTarget Prediction Using LowRank Embeddings: Theory & Practice, Keynote Talk, ECML, 2017
[pdf]
 Bilinear Prediction using LowRank Models, Keynote Talk, ALT, 2015
[pdf]
 Proximal Newton Methods for LargeScale Machine Learning, Distinguished Talk, Shanghai Tech, 2015
[pdf]
 DivideandConquer Methods for LargeScale Data Analysis, Keynote Talk, ICMLA, 2014
[pdf]
 NOMAD: A Distributed Framework for Latent Variable Models, Invited Talk, NIPS Workshop, 2014
[pdf]
 Asynchronous Matrix Completion, Plenary Talk, Householder Symposium, 2014
[pdf]
 Informatics in Computational Medicine, ICES Computational Medicine Day, 2014
[pdf]
 Scalable Network Analysis, Keynote Talk, COMAD, 2013
[pdf]
 Fast and Accurate Low Rank Approximation of Massive Graphs
[pdf]
 Guaranteed Rank Minimization with Singular Value Projection
[pdf]
 Matrix Computations in Machine Learning
[pdf]
 The LogDet Divergence and its Applications
[pdf]
 Metric and Kernel Learning
[pdf]
 Machine Learning with Bregman Divergences
[pdf]
 SIAM Linear Algebra Prize Talk: Orthogonal Eigenvectors and Relative Gaps
[pdf]
 LowRank Kernel Learning with Bregman Matrix Divergences
[pdf (short version)]
[pdf (longer version)]
 Normalized Cuts without Eigenvectors: A Multilevel Approach
[pdf]
 Matrix Nearness Problems Using Bregman Divergences
[pdf]
 Fast Eigenvalue/Eigenvector Computation for Dense Symmetric Matrices
[pdf]
 Inverse Eigenvalue Problems in Wireless Communications
[pdf]
 Information Theoretic Clustering, Coclustering and Matrix Approximations
[powerpoint]


