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Research InterestsRuslan Salakhutdinov is a PhD student at University of Toronto. His broad research interests involve developing learning and inference algorithms for probabilistic hierarchical models that contain many layers of nonlinear processing. Much of his current research concentrates on the theoretical analysis of Deep Belief Networks and Deep Boltzmann Machines, with applications to information retrieval, visual object recognition, and dimensionality reduction. His other interests include matrix factorization, approximate inference and learning of large scale graphical models, and large scale optimization.[ Home | Information | Research | Background ] Ruslan Salakhutdinov, Artificial Intelligence Group, Toronto Computer Science || www.cs.toronto.edu/~rsalakhu |