Ruslan Salakhutdinov

Microsoft Faculty Fellow
Sloan Fellow
Carnegie Mellon University
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:

Recent Papers:

  • Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification.
    Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov

  • End-to-End Multihop Retrieval for Compositional Question Answering over Long Documents
    Haitian Sun, William W. Cohen, Ruslan Salakhutdinov

  • 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]