Ruslan Salakhutdinov, Assistant Professor

Department of Statistics,
Department of Computer Science (by courtesy)
University of Toronto
100 St. George Street, 6th floor
Sidney Smith Hall, Room 6002
Toronto, Ontario M5S 3G3, Canada

Email: rsalakhu (at) utstat (dot) toronto (dot) edu

Quick link to my research papers and invited talks.

I am teaching

STA 4273H (Fall 2011): Research Topics In Statistical Machine Learning

STAD37H (Winter 2012): Statistical Multivariate Analysis

I will serve as an Area Chair for the NIPS 2012 program committee.

I will serve as an Area Chair for the ICML 2012.

I will serve as a Workshop Chair for the UAI 2012.

I am a guest editor for TPAMI Special Issue on Learning Deep Architectures.

Recent Papers:

Deep Lambertian Networks
Yichuan Tang , Ruslan Salakhutdinov, and Geoffrey Hinton
To appear in The 29th International Conference on Machine Learning (ICML 2012)

Deep Mixtures of Factor Analysers
Yichuan Tang , Ruslan Salakhutdinov, and Geoffrey Hinton
To appear in The 29th International Conference on Machine Learning (ICML 2012)

Concept learning as motor program induction: A large-scale empirical study.
Brenden Lake , Ruslan Salakhutdinov, and Josh Tenenbaum.
Proceedings of the 34rd Annual Conference of the Cognitive Science Society, 2012 [ pdf], Supporting Info

Robust Boltzmann Machines for Recognition and Denoising
Yichuan Tang , Ruslan Salakhutdinov, and Geoffrey Hinton
To appear in IEEE Computer Vision and Pattern Recognition (CVPR) 2012. [ pdf]

One-Shot Learning with a Hierarchical Nonparametric Bayesian Model
Ruslan Salakhutdinov, Josh Tenenbaum, and Antonio Torralba
To appear in JMLR WC&P Unsupervised and Transfer Learning, 2012, Preprint [ pdf]

An Efficient Learning Procedure for Deep Boltzmann Machines
Ruslan Salakhutdinov and Geoffrey Hinton
To appear in Neural Computation, 2012

Domain Adaptation: A Small Sample Statistical Approach
Dean Foster, Sham Kakade, and Ruslan Salakhutdinov
To appear in JMLR W&CP 16 (AI & Statistics), 2012 [ pdf]

Resource Configurable Spoken Query Detection using Deep Boltzmann Machines
Yaodong Zhang, Ruslan Salakhutdinov, Hung-An Chang, and James Glass.
37th International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2012 [ pdf]

Learning to Learn with Compound Hierarchical-Deep Models
Ruslan Salakhutdinov, Josh Tenenbaum , Antonio Torralba
Neural Information Processing Systems (NIPS 25), 2012 [ pdf]

Transfer Learning by Borrowing Examples
Joseph Lim , Ruslan Salakhutdinov Antonio Torralba
Neural Information Processing Systems (NIPS 25), 2012 [ pdf] [ Project Page]

Learning with the Weighted Trace-norm under Arbitrary Sampling Distributions
Rina Foygel, Ruslan Salakhutdinov Ohad Shamir, Nathan Srebro
Neural Information Processing Systems (NIPS 25), 2012 [ pdf]
Supplementary material [ pdf]

One-shot learning of simple visual concepts
Brenden Lake , Ruslan Salakhutdinov, Jason Gross, and Josh Tenenbaum.
Proceedings of the 33rd Annual Conference of the Cognitive Science Society, 2011 [ pdf], videos

Learning to Share Visual Appearance for Multiclass Object Detection
Ruslan Salakhutdinov, Antonio Torralba , and Josh Tenenbaum.
IEEE Computer Vision and Pattern Recognition (CVPR) 2011 [ pdf]

Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm.
Ruslan Salakhutdinov and Nathan Srebro.
Neural Information Processing Systems 24, 2011 [ pdf]

Practical Large-Scale Optimization for Max-Norm Regularization.
Jason Lee, Benjamin Recht, Ruslan Salakhutdinov, Nathan Srebro, and Joel A. Tropp.
Neural Information Processing Systems 24, 2011 [ pdf]

Ruslan Salakhutdinov, Department of Statistics, University of Toronto, http://www.utstat.toronto.edu/~rsalakhu/