Learning Deep Unsupervised and Multimodal Models

Speaker: Ruslan Salakhutdinov , Carnegie Mellon University (CMU)

Date: Wednesday, April 05, 2017

Time: 4:00 PM to 5:15 PM Note: all times are in the Eastern Time Zone

Public: Yes

Location: 34-101

Event Type:

Room Description:

Host: Stefanie Jegelka, MIT EECS

Contact: Stefanie S. Jegelka, stefje@csail.mit.edu

Relevant URL:

Speaker URL: None

Speaker Photo:
None

Reminders to: seminars@csail.mit.edu

Reminder Subject: TALK: Ruslan Salakhutdinov: Learning Deep Unsupervised and Multimodal Models

In this talk I will first introduce a broad class of unsupervised deep learning models and show that they can learn useful hierarchical representations from large volumes of high-dimensional data with applications in information retrieval, object recognition, and speech perception. I will next introduce deep models that are capable of extracting a unified representation that fuses together multiple data modalities and present the Reverse Annealed Importance Sampling Estimator (RAISE) for evaluating these deep generative models. Finally, I will discuss models that can generate natural language descriptions (captions) of images and generate images from captions using attention, as well as introduce multiplicative and fine-grained gating mechanisms with application to reading comprehension.

Bio: Ruslan Salakhutdinov received his PhD in 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 Departments of Statistics and Computer Science. In 2016 he joined the Machine Learning Department at Carnegie Mellon University as an Associate Professor. Ruslan's primary interests lie in deep learning, machine learning, and large-scale optimization. He is an Alfred P. Sloan Research Fellow, Microsoft Research Faculty Fellow, Canada Research Chair in Statistical Machine Learning, a recipient of the Early Researcher Award, Google Faculty Award, Nvidia's Pioneers of AI award, and is a Senior Fellow of the Canadian Institute for Advanced Research.

Research Areas:

Impact Areas:

See other events that are part of the Machine Learning Seminar Series.

Created by Stefanie S. Jegelka Email at Friday, March 24, 2017 at 5:03 PM.