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ANC/DTC Seminar: Ruslan Salakhutidnov, University of Toronto (Host: Iain Murray)

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Learning Structured, Robust, and Multimodal Models

  • ANC/DTC Seminar
When May 06, 2014
from 11:00 AM to 12:00 PM
Where IF G.07
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Building intelligent systems that are capable of extracting meaningful representations from high-dimensional data lies at the core of solving many Artificial Intelligence tasks, including visual object recognition, information retrieval, speech perception, and language understanding.

In this talk I will first introduce a broad class of hierarchical probabilistic models called Deep Boltzmann Machines (DBMs) and show that DBMs can learn useful hierarchical representations from large volumes of high-dimensional data with applications in information retrieval, object recognition, and speech perception. I will then describe a new class of more complex models that combine Deep Boltzmann Machines with structured hierarchical Bayesian models and show how these models can learn a deep hierarchical structure for sharing knowledge across hundreds of visual categories, which allows accurate learning of novel visual concepts from few examples. Finally, I will introduce deep models that are capable of extracting a unified representation that fuses together multiple data modalities. I will show that on several tasks, including modelling images and text, video and sound, these models significantly improve upon many of the existing techniques.




Ruslan Salakhutdinov received his PhD in machine learning (computer science) from the University of Toronto in 2009. After spending two post-doctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an Assistant Professor in the Department of Computer Science and Department of Statistics. Dr. Salakhutdinov's primary interests lie in statistical machine learning, Bayesian statistics, Deep Learning, and large-scale optimization. He is the recipient of the Early Researcher Award, Connaught New Researcher Award, Alfred P. Sloan Research Fellowship, Microsoft Faculty Fellowship, Google Faculty Award, and a Fellow of the Canadian Institute for Advanced Research.