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GRASP Special Seminar: Alexander Schwing, University of Toronto, “Parallel Inference and Learning with Deep Structured Distributions”

October 2, 2015 @ 2:00 pm - 3:00 pm


Many problems in real-world applications involve predicting several random variables which are statistically related. A structured model, like a Markov random field (MRF), is a great mathematical tool to encode those dependencies.
Within the first part of this talk I will discuss the difficulties in finding the most likely configuration described by a structured distribution. Subsequently I will present a model-parallel inference algorithm and demonstrate its effectiveness by jointly estimating the disparity of more than 12 million variables.
In the second part, I will show how to combine structured distributions with deep learning algorithms to estimate complex representations while taking into account the dependencies between the output variables. To estimate those deep structured distributions I will discuss a sample-parallel training algorithm that is able to learn structured models jointly with deep features. I will then illustrate its applicability by using, among others, a 3D scene understanding task.


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Alexander Schwing’s research interests are optimization algorithms (e.g., primal-dual methods), statistical models like structured predictors and parallelization of implementations for high performance computing environments. Interesting playground for all three fields are inference and structured prediction in machine learning as well as computer vision, and in particular 3D scene understanding. He is currently working with Prof. Ruslan Salakhutdinov and Prof. Raquel Urtasun as a postdoc within the machine learning group at University of Toronto, Computer Science department.

In 2014, Alexander completed his PhD under supervision of Prof. Marc Pollefeys, Prof. Tamir Hazan and Prof. Raquel Urtasun within the Computer Vision and Geometry (CVG) group of the computer science department of ETH Zurich (ETHZ). He also received his Diploma (Master) majoring in electrical engineering with a focus on signal processing from Technical University of Munich (TUM).


October 2, 2015
2:00 pm - 3:00 pm
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