Home Bio Teaching Publications Talks Software Students Miscellaneous Selected Talks Multi-Output 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] Multi-Target Prediction Using Low-Rank Embeddings: Theory & Practice, Keynote Talk, ECML, 2017 [pdf] 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