Ruslan Salakhutdinov

Ruslan Salakhutdinov

Professor
Microsoft Faculty Fellow
Sloan Fellow
Carnegie Mellon University
rsalakhu[at]cs.cmu.edu
CV Google Scholar  

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]