I am a UPMC professor of Computer Science in the
Machine Learning Department,
School of Computer Science
at Carnegie Mellon University.
I work in the field of statistical machine learning (See my
CV.)
My research interests include
Deep Learning,
Probabilistic Graphical Models, and
Large-scale Optimization.
Prospective students: Please
read this to ensure that I read your email.
Recent Research Highlights:
- 4 part Deep Learning Tutorial at the Simons Institute, Berkeley
Part 1:[Slides (pdf)], Part 2:[Slides (pdf)], Part 3:[Slides (pdf)], Part 4:[Slides (pdf)].
- Deep Learning Tutorial, MLSS, Tübingen, Germany
Part 1:[Slides (pdf)], Part 2:[Slides (pdf)].
- I am co-teaching a Intermdiate Deep Learning class, Fall 2020.
Recent Papers:
-
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification.
Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov
[arXiv] -
End-to-End Multihop Retrieval for Compositional Question Answering over Long Documents
Haitian Sun, William W. Cohen, Ruslan Salakhutdinov
[arXiv] -
Towards Understanding and Mitigating Social Biases in Language Models
Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, Ruslan Salakhutdinov
ICML 2021 [arXiv] -
Information Obfuscation of Graph Neural Networks
P. Liao, H. Zhao, K. Xu, T. Jaakkola, G. Gordon, S. Jegelka and R. Salakhutdinov
ICML 2021 [arXiv] -
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
Haitian Sun, Patrick Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William Cohen
ICML 2021 [arXiv] -
Instabilities of Offline RL with Pre-Trained Neural Representation
Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham M. Kakade
ICML 2021 [arXiv] -
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers.
Benjamin Eysenbach*, Swapnil Asawa*, Shreyas Chaudhari*, Sergey Levine, Ruslan Salakhutdinov
International Conference on Learning Representations (ICLR) 2021. [arXiv] -
Self-supervised Representation Learning with Relative Predictive Coding
Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov.
International Conference on Learning Representations (ICLR) 2021. [arXiv] -
Self-supervised Learning from a Multi-view Perspective
Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, Louis-Philippe Morency.
International Conference on Learning Representations (ICLR) 2021. [arXiv] -
C-Learning: Learning to Achieve Goals via Recursive Classification.
Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
International Conference on Learning Representations (ICLR) 2021. [arXiv] -
Planning with Submodular Objective Functions
Ruosong Wang, Hanrui Zhang, Devendra Singh Chaplot, Denis Garagić, Ruslan Salakhutdinov
arXiv [arXiv] -
Exploring Controllable Text Generation Techniques
Shrimai Prabhumoye, Alan W Black, Ruslan Salakhutdinov.
28th International Conference on Computational Linguistics (COLING) 2020, [arXiv] -
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement
Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov
NeurIPS 2020, oral, [arXiv] -
Object Goal Navigation using Goal-oriented Semantic Exploration
Devendra Singh Chaplot, Dhiraj Gandhi, Abhinav Gupta, Ruslan Salakhutdinov.
NeurIPS 2020, [arXiv] -
Neural Methods for Point-wise Dependency Estimation
Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov.
NeurIPS 2020, [arXiv] -
On Reward-Free Reinforcement Learning with Linear Function Approximation
Ruosong Wang, Simon S. Du, Lin F. Yang, Ruslan Salakhutdinov
NeurIPS 2020, [arXiv] -
Neural Topological SLAM for Visual Navigation
Devendra Singh Chaplot, Ruslan Salakhutdinov, Abhinav Gupta, Saurabh Gupta.
CVPR 2020, [arXiv]