Ruslan Salakhutdinov

Associate Professor
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:

  • GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations
    Zhilin Yang, Jake Zhao, Bhuwan Dhingra, Kaiming He, William Cohen, Ruslan Salakhutdinov, Yann LeCun
    NIPS 2018, [arXiv]

  • Deep Generative Models with Learnable Knowledge Constraints
    Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Xiaodan Liang, Lianhui Qin, Haoye Dong, Eric Xing
    NIPS 2018, [arXiv]

  • How Many Samples are Needed to Learn a Convolutional Neural Network?
    Simon Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnani, Ruslan Salakhutdinov, Aarti Singh
    NIPS 2018, [arXiv]

  • HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
    Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, Christopher Manning
    EMNLP, 2018, [arXiv], [Code, Data]

  • Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text
    Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, William Cohen
    EMNLP, 2018, [arXiv], [Code]

  • Investigating the Working of Text Classifiers
    Devendra Singh Sachan, Manzil Zaheer, Ruslan Salakhutdinov
    COLING 2018, [arXiv]

  • Structured Control Nets for Deep Reinforcement Learning
    Mario Srouji, Jian Zhang, Ruslan Salakhutdinov
    ICML 2018, [arXiv]

  • Gated Path Planning Networks
    Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric Xing, Ruslan Salakhutdinov
    ICML 2018, [arXiv], [Code].

  • Transformation Autoregressive Networks
    Junier B. Oliva, Avinava Dubey, Manzil Zaheer, BarnabásPoczos, Ruslan Salakhutdinov, Eric P. Xing, eff Schneider
    ICML 2018, [arXiv]

  • Learning Cognitive Models using Neural Networks, (oral)
    Devendra Singh Chaplot, Christopher MacLellan, Ruslan Salakhutdinov, Kenneth Koedinger.
    [arXiv],, 19th International Conference on Artificial Intelligence in Education (AIED-18), London, UK

  • Style Transfer Through Back-Translation
    Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov and Alan Black
    ACL 2018 [arXiv], [Code].

  • Neural Models for Reasoning over Multiple Mentions using Coreference
    Bhuwan Dhingra, Qiao Jin, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov
    NAACL, 2018 (Short Paper) [arXiv].

  • Global Pose Estimation with an Attention-based Recurrent Network
    Emilio Parisotto, Devendra Singh Chaplot, Jian Zhang, Ruslan Salakhutdinov
    CVPR 2018 workshop on Deep Learning for Visual SLAM [arXiv], 2018, best paper award .

  • On Characterizing the Capacity of Neural Networks using Algebraic Topology
    William H. Guss, Ruslan Salakhutdinov
    [arXiv], 2018.

  • Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
    Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen
    ICLR 2018, oral, [arXiv], [code].

  • Active Neural Localization
    Devendra Singh Chaplot, Emilio Parisotto, Ruslan Salakhutdinov
    ICLR 2018 [arXiv], [code].

  • Neural Map: Structured Memory for Deep Reinforcement Learning
    Emilio Parisotto, Ruslan Salakhutdinov
    ICLR 2018, [arXiv], ICLR 2018.

  • On Unifying Deep Generative Models
    Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing
    ICLR 2018 [arXiv].

  • Selecting the Best in GANs Family: a Post Selection Inference Framework
    Yao-Hung Hubert Tsai, Denny Wu, Makoto Yamada, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu
    [arXiv], ICLR workshop 2018.

  • A Generic Approach for Escaping Saddle Points
    Sashank J Reddi, Manzil Zaheer, Suvrit Sra, Barnabas Poczos, Francis Bach, Ruslan Salakhutdinov, Alexander J Smola
    [arXiv], AIStats 2018.

  • Gated-Attention Architectures for Task-Oriented Language Grounding
    Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, Ruslan Salakhutdinov
    [arXiv], AAAI 2018, oral.

  • Knowledge-based Word Sense Disambiguation using Topic Models
    Devendra Singh Chaplot, Ruslan Salakhutdinov
    [pdf], AAAI 2018, oral.

  • A Comparative Study of Word Embeddings for Reading Comprehension
    Bhuwan Dhingra, Hanxiao Liu, Ruslan Salakhutdinov, William W. Cohen
    [arXiv], 2017.

  • Good Semi-supervised Learning that Requires a Bad GAN
    Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov
    NIPS 2017, [arXiv].

  • Deep Sets
    Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan Salakhutdinov, Alexander Smola
    NIPS 2017, oral [arXiv].

  • Geometry of Optimization and Implicit Regularization in Deep Learning
    Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro
    Survey paper, [arXiv].

  • Deep Conditional Determinantal Point Process for Large-Scale Multi-Label Classification
    P. Xie, R. Salakhutdinov, L. Mou and E.P. Xing
    ICCV 2017.

  • Learning Robust Visual-Semantic Embeddings
    Yao-Hung Hubert Tsai, Liang-Kang Huang, Ruslan Salakhutdinov
    ICCV 2017, [arXiv].

  • Improved Variational Autoencoders for Text Modeling using Dilated Convolutions
    Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, Taylor Berg-Kirkpatrick
    ICML 2017, [arXiv].

  • Controllable Text Generation
    Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing
    ICML 2017, [arXiv].

  • Semi-Supervised QA with Generative Domain-Adaptive Nets
    Zhilin Yang, Junjie Hu, Ruslan Salakhutdinov, William W. Cohen
    ACL 2017, arXiv].

  • Gated-Attention Readers for Text Comprehension
    Bhuwan Dhingra, Hanxiao Liu, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov
    ACL 2017, [arXiv], [Code].

  • The More You Know: Using Knowledge Graphs for Image Classification
    Kenneth Marino, Ruslan Salakhutdinov, Abhinav Gupta
    CVPR 2017, [arXiv].

  • Spatially Adaptive Computation Time for Residual Networks
    Michael Figurnov, Maxwell D. Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry Vetrov, Ruslan Salakhutdinov
    CVPR 2017, [arXiv], [Code].

  • Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks
    Zhilin Yang, Ruslan Salakhutdinov, William W. Cohen
    ICLR 2017, [arXiv].

  • On the Quantitative Analysis of Decoder-Based Generative Models
    Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger Grosse
    ICLR 2017, [arXiv], [Code].

  • Words or Characters? Fine-grained Gating for Reading Comprehension
    Zhilin Yang, Bhuwan Dhingra, Ye Yuan, Junjie Hu, William W. Cohen, Ruslan Salakhutdinov
    ICLR 2017, [arXiv].