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)].
  
  
  
  
  
  
  
  

  Recent Papers:

  • VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks
    Jing Yu Koh, Robert Lo, Lawrence Jang, Vikram Duvvur, Ming Chong Lim, Po-Yu Huang, Graham Neubig, Shuyan Zhou, Ruslan Salakhutdinov, Daniel Fried
    ACL 2014 [arXiv] [Code]

  • Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks,
    Murtaza Dalal, Tarun Chiruvolu, Devendra Chaplot, Ruslan Salakhutdinov
    ICLR 2024 [arXiv] [Code]

  • Effective Data Augmentation With Diffusion Models
    Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov
    ICLR 2024 [arXiv] [code]

  • Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications
    Paul Pu Liang, Chun Kai Ling, Yun Cheng, Alex Obolenskiy, Yudong Liu, Rohan Pandey, Alex Wilf, Louis-Philippe Morency, Ruslan Salakhutdinov
    ICLR 2024 [arXiv] [code]

  • Contrastive Difference Predictive Coding
    Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach
    ICLR 2024 [arXiv] [code]

  • Manifold Preserving Guided Diffusion
    Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim♨, Wei-Hsiang Liao, Yuki Mitsufuji, Zico Kolter, Ruslan Salakhutdinov, Stefano Ermon
    ICLR 2024 [arXiv] [code]

  • Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
    Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine
    ICLR 2024 [arXiv] [code]

  • Confronting Reward Model Overoptimization with Constrained RLHF
    Ted Moskovitz, Aaditya K. Singh, DJ Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca D. Dragan, Stephen McAleer
    ICLR 2024 [arXiv]

  • Generating Images with Multimodal Language Models
    Jing Yu Koh, Daniel Fried, Ruslan Salakhutdinov
    NeurIPS 2023, [arXiv] [code]

  • Factorized Contrastive Learning: Going Beyond Multi-view Redundancy
    Paul Pu Liang*, Zihao Deng*, Martin Ma*, James Zou, Louis-Philippe Morency, Ruslan Salakhutdinov
    NeurIPS 2023, [arXiv] [code]

  • Quantifying & Modeling Feature Interactions: An Information Decomposition Framework
    Paul Pu Liang, Yun Cheng, Xiang Fan, Chun Kai Ling, Suzanne Nie, Richard Chen, Zihao Deng, Nicholas Allen, Randy Auerbach, Faisal Mahmood, Ruslan Salakhutdinov, Louis-Philippe Morency
    NeurIPS 2023, [arXiv] [code]

  • Imitating Task and Motion Planning with Visuomotor Transformers
    Murtaza Dalal*, Ajay Mandlekar, Caelan Garrett, Ankur Handa, Ruslan Salakhutdinov, Dieter Fox
    CoRL 2023, [arXiv] [code]

  • Graph Generative Model for Benchmarking Graph Neural Networks
    Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov
    ICML 2023 [arXiv]

  • A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
    Benjamin Eysenbach, Matthieu Geist, Sergey Levine, and Ruslan Salakhutdinov
    ICML 2023 [arXiv]

  • Grounding Language Models to Images for Multimodal Inputs and Outputs
    Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried
    ICML 2023 [arXiv] [code]

  • Multimodal Fusion Interactions: A Study of Human and Automatic Quantification
    Paul Pu Liang, Yun Cheng, Ruslan Salakhutdinov, Louis-Philippe Morency
    ICMI 2023 [arXiv] [code]