Inderjit S. Dhillon's Talks Selected Talks

  • Bilinear Prediction using Low-Rank Models, Keynote Talk, ALT 2015 [pdf]
  • Proximal Newton Methods for Large-Scale Machine Learning, Distinguished Talk, Shanghai Tech, 2015 [pdf]
  • Divide-and-Conquer Methods for Large-Scale 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]
  • Low-Rank 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, Co-clustering and Matrix Approximations [powerpoint]

Department of Computer Science University of Texas at Austin