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:

  • 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]

  • Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension
    Ruosong Wang, Ruslan Salakhutdinov, Lin F. Yang
    NeurIPS 2020, [arXiv]

  • Planning with General Objective Functions: Going Beyond Total Rewards
    Ruosong Wang, Peilin Zhong, Simon S. Du, Ruslan Salakhutdinov, Lin F. Yang
    NeurIPS 2020, [arXiv]

  • A Closer Look at Robustness vs. Accuracy
    Yao-Yuan Yang, Cyrus Rashtchian, Hongyang Zhang, Ruslan Salakhutdinov and Kamalika Chaudhuri
    NeurIPS 2020, [arXiv]

  • Weakly-Supervised Reinforcement Learning for Controllable Behavior [arXiv]
    Lisa Lee, Benjamin Eysenbach, Ruslan Salakhutdinov, Shane Gu, Chelsea Finn
    NeurIPS 2020, [arXiv]

  • Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis
    Yao-Hung Hubert Tsai*, Martin Q. Ma*, Muqiao Yang*, Ruslan Salakhutdinov, Louis-Philippe Morency.
    Empirical Methods in Natural Language Processing (EMNLP) 2020, [arXiv]

  • Neural Topological SLAM for Visual Navigation
    Devendra Singh Chaplot, Ruslan Salakhutdinov, Abhinav Gupta, Saurabh Gupta.
    CVPR 2020, [arXiv]

  • Topological Sort for Sentence Ordering
    Shrimai Prabhumoye, Ruslan Salakhutdinov, Alan W Black.
    ACL 2020, [arXiv]

  • Politeness Transfer: A Tag and Generate Approach
    Aman Madaan*, Amrith Setlur*, Tanmay Parekh*, Barnabas Poczos, Graham Neubig,Yiming Yang, Ruslan Salakhutdinov, Alan W Black, Shrimai Prabhumoye.
    ACL 2020, [arXiv]

  • Towards Debiasing Sentence Representations
    Paul Pu Liang, Irene Li, Emily Zheng, Yao Chong Lim, Ruslan Salakhutdinov, Louis-Philippe Morency
    ACL 2020, [arXiv]

    Geometric Capsule Autoencoders for 3D Point Clouds Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov

  • Geometric Capsule Autoencoders for 3D Point Clouds
    Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov
    arXiv 2020, [arXiv]

  • Capsules with Inverted Dot-Product Attention Routing
    Yao-Hung Hubert Tsai, Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov
    ICLR 2020, [arXiv]

  • Learning To Explore Using Active Neural Mapping
    Devendra Singh Chaplot, Saurabh Gupta, Dhiraj Gandhi, Abhinav Gupta, Ruslan Salakhutdinov
    ICLR 2020, [arXiv]

  • Differentiable Reasoning over a Virtual Knowledge Base
    Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, William W. Cohen
    ICLR 2020, [arXiv]

  • Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks
    Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu
    ICLR 2020, [arXiv]

  • On Emergent Communication in Competitive Multi-Agent Teams
    Paul Pu Liang, Jeffrey Chen, Ruslan Salakhutdinov, Louis-Philippe Morency, Satwik Kottur
    AAMAS 2020.

  • Modular Visual Navigation using Active Neural Mapping
    Devendra Singh Chaplot, Saurabh Gupta, Abhinav Gupta, Ruslan Salakhutdinov
    [pdf] [Videos], Winner of the Habitat Navigation Challenge at CVPR 2019.

  • Concurrent Episodic Meta Reinforcement Learning
    Emilio Parisotto, Soham Ghosh, Sai Bhargav Yalamanchi, Varsha Chinnaobireddy, Yuhuai Wu, Ruslan Salakhutdinov

  • Efficient Exploration via State Marginal Matching
    Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric Xing, Sergey Levine, Ruslan Salakhutdinov
    [arXiv] [Code]

  • Worst cases policy gradients
    Charlie Tang, Jian Zhang, Ruslan Salakhutdinov
    CoRL 2019

  • Transformer Dissection: A Unified Understanding of Transformer Attention via the Lens of Kernel
    Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov
    EMNLP 2019, [arXiv]

  • Multiple Futures Prediction
    Charlie Tang, Ruslan Salakhutdinov
    NeurIPS 2019, [arXiv]

  • Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
    Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
    NeurIPS 2019, [arXiv] [Code]

  • Learning Data Manipulation for Augmentation and Weighting
    Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom Mitchell, Eric P. Xing
    NeurIPS 2019

  • Mixtape: Breaking the Softmax Bottleneck Efficiently
    Zhilin Yang, Thang Luong, Ruslan Salakhutdinov, Quoc V Le
    NeurIPS 2019

  • XLNet: Generalized Autoregressive Pretraining for Language Understanding
    Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V. Le
    NeurIPS 2019 [arXiv] [Code], oral,

  • Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
    Simon S. Du, Kangcheng Hou, Barnabás Póczos, Ruslan Salakhutdinov, Ruosong Wang, Keyulu Xu
    NeurIPS 2019 [arXiv]

  • On Exact Computation with an Infinitely Wide Neural Net
    Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang
    NeurIPS 2019 [arXiv]

  • Learning Neural Networks with Adaptive Regularization
    Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon
    NeurIPS 2019 [arXiv]

  • Deep Gamblers: Learning to Abstain with Portfolio Theory
    Liu Ziyin, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda
    NeurIPS 2019 [arXiv]

  • MineRL: A Large-Scale Dataset of Minecraft Demonstrations
    William H. Guss, Brandon Houghton, Nicholay Topin, Phillip Wang, Cayden Codel, Manuela Veloso, Ruslan Salakhutdinov
    IJCAI 2019 [arXiv], [Web]

  • My Way of Telling a Story": Persona based Grounded Story Generation
    Shrimai Prabhumoye, Khyathi Chandu, Ruslan Salakhutdinov, Alan W Black.
    Storytelling Workshop at ACL 2019 [arXiv],

  • Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
    Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V. Le, Ruslan Salakhutdinov
    ACL 2019 [arXiv], [Code]

  • Multimodal Transformer for Unaligned Multimodal Language Sequences
    Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, Zico Kolter, Louis-Philippe Morency, Ruslan Salakhutdinov
    ACL 2019 [arXiv], [Code]

  • Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization
    Paul Pu Liang, Zhun Liu, Yao-Hung Hubert Tsai, Qibin Zhao, Ruslan Salakhutdinov, Louis-Philippe Morency
    ACL 2019 [arXiv]

  • The Omniglot Challenge: A 3-Year Progress Report
    Brenden M. Lake, Ruslan Salakhutdinov, Joshua B. Tenenbaum
    Current Opinion in Behavioral Sciences, 2019 [arXiv]

  • Embodied Multimodal Multitask Learning
    Devendra Singh Chaplot, Lisa Lee, Ruslan Salakhutdinov, Devi Parikh, Dhruv Batra

  • Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph
    Yao-Hung Hubert Tsai, Santosh Kumar Divvala, Louis-Philippe Morency, Ruslan Salakhutdinov, Ali Farhadi
    CVPR 2019, [arXiv]

  • A Strong and Simple Baseline for Multimodal Utterance Embeddings
    Paul Pu Liang, Yao Chong Lim, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Louis-Philippe Morency
    NAACL 2019, [arXiv] [Code]

  • Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex
    Hongyang Zhang, Junru Shao, Ruslan Salakhutdinov
    AIStats 2019, [arXiv]

  • Learning Factorized Multimodal Representations
    Yao Hung Tsai, Paul Pu Liang, Amir Ali Bagherzade, Louis-Philippe Morency, Ruslan Salakhutdinov
    ICLR 2019, [arXiv] [Code]

  • AutoLoss: Learning Discrete Schedule for Alternate Optimization
    Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric Xing
    ICLR 2019, [arXiv]

  • Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator
    Makoto Yamada, Yi Wu, Yao Hung Tsai, Hirofumi Ohtai, Ruslan Salakhutdinov, Ichiro Takeeuchi, Kenji Fukumizu
    ICLR 2019, [arXiv]

  • Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function
    Devendra Singh Sachan, Manzil Zaheer, Ruslan Salakhutdinov
    AAAI 2019, [pdf]