Tengyu Ma

Hi! I am currently a visiting scientist at Facebook AI Research, located in Menlo Park. I was a Ph.D. student at Computer Science Department, Princeton University, advised by Professor Sanjeev Arora. My research interests broadly include topics in machine learning and algorithms, such as non-convex optimization, deep learning, representation learning (for natural language processing), distributed optimization, convex relaxation (e.g. sum of squares hierarchy), and high-dimensional statistics. Before coming to U.S., I studied at Andrew Chi-Chih Yao's CS pilot class at Tsinghua University.
I'm thrilled to be joining Stanford University as an assistant professor in the Fall of 2018! (I'm also currently visiting Stanford every Wed.)
E-mail: firstname + lastname at cs dot stanford dot edu
    2016             NIPS best student paper award
    2017.01-05  Simons-Berkeley Research Fellowship
    2016-2017   Siebel Scholarship
    2016-2017   Princeton Honorific Fellowship
    2015            Wu Prize for Excellence
    2015-2016   IBM PhD Fellowship
    2014-2016   Simons Award for Graduate Students in Theoretical Computer Science
    2010.12      8th Place in Putnam Mathematical Competition (Putnam10)
    2007.07       Silver Medal in 47th International Mathematical Olympiad (IMO07)
    Linear Algebraic Structure of Word Senses, with Applications to Polysemy
    with Sanjeev Arora, Yuanzhi Li, Yingyu Liang, and Andrej Risteski
    manuscript, 2016  
    with Moritz Hardt and Benjamin Recht
    manuscript (submitted to JMLR)  
    Optimal Design of Process Flexility for General Production Systems
    Xi Chen, Tengyu Ma, Jiawei Zhang, Yuan Zhou
    manuscript (submitted to Operations research)  
    with Rong Ge
    NIPS 2017 (oral), to appear. (best paper in the NIPS 2016 workshop on nonconvex optimization for ML) 
    with Sanjeev Arora, Rong Ge, Yingyu Liang, and Yi Zhang
    ICML, 2017  
    with Moritz Hardt
    International Conference on Learning Representations (ICLR) 2017  
    with Sanjeev Arora and Yingyu Liang
    International Conference on Learning Representations (ICLR) 2017  
    Jason Lee, Qihang Lin, Tengyu Ma, Tianbao Yang
    to appear in JMLR  
    with Naman Agarwal, Zeyuan Allen-Zhu, Brian Bullins, and Elad Hazan
    STOC 2017  
    with Sanjeev Arora, Rong Ge, and Andrej Risteski
    STOC 2017  
    with Rong Ge and Jason D. Lee
    NIPS (best student paper award), 2016  
    with Elad Hazan
    NIPS 2016  
    with Jonathan Shi and David Steurer
    FOCS 2016  
    with Sanjeev Arora, Rong Ge, Frederic Koehler, and Ankur Moitra
    ICML 2016  
    with Sanjeev Arora, Yuanzhi Li, Yingyu Liang, and Andrej Risteski
    Transactions of the Association for Computational Linguistics (TACL), 4:385-399, 2016  
    with Mark Braverman, Ankit Garg, Huy L. Nguyen, and David P. Woodruff
    STOC 2016  
    with Avi Wigderson
    NIPS 2015  
    with Sanjeev Arora and Yingyu Liang
    ICLR workshop, 2016  
    with Rong Ge
    RANDOM/APPROX 2015  
    with Dan Garber and Elad Hazan
    ICML 2015  
    with Sanjeev Arora, Rong Ge, and Ankur Moitra
    COLT 2015  
    with Ankit Garg and Huy Nguyễn
    NIPS 2014 (oral)  
    with Sanjeev Arora, Aditya Bhaskara, and Rong Ge
    ICML 2014 
    with Bo Tang and Yajun Wang
    Theory of Computing Systems, 2016  
    Proceedings of 30th Symposium on Theoretical Aspects of Computer Science (STACS 2013) 
blog posts:
    Back-propagation, an introduction (with Sanjeev Arora)
Sanjeev's posts regarding our word embedding works
    On the Optimization Landscape of Matrix and Tensor Decomposition Problems
    Simons Institute, Sept 2017, Berkeley, USA
    Generalization and Equilibrium in Generative Adversarial Nets (GANs)
    OpenAI, May 2017, San Francisco, USA
    Better Understanding of Non-convex Methods in Machine Learning
    Stanford Statistics Department Seminar, Jan 2017, Stanford, USA
    MIT EECS Special Seminar, Feb 2017, Cambridge, USA
    Stanford CS Seminar, Feb 2017, Stanford, USA
    Berkeley CS Seminar, Mar 2017, Berkeley, USA
    Columbia CS Seminar, Mar 2017, NYC, USA
    CMU CSC Seminar, Mar 2017, Pittsburgh, USA
    Caltech CMS Special Seminar, Mar 2017, Pasadena, USA
    UW Computer Science Engineering Colloquium, April 2017, Seattle, USA
    OpenAI, April 2017, San Francisco, USA
    Facebook AI Research, May 2017, Menlo Park, USA
    Analyzing Non-convex Optimization: Matrix Completion and Linear Residual Networks
    MIT algorithms and complexity seminar, Dec 2016, Cambridge, USA
    Stanford ML lunch, Nov 2016, Stanford, USA
    MSR Talks Series, Nov 2016, Redmond, USA
    Matrix Completion has No Spurious Local Minimum
    NIPS, Dec 2016, Barcelona, Spain
    Columbia theory seminar, Oct 2016, New York City, USA
    Yale YNPG seminar, Oct 2016, New Haven, USA
    Bekeley, Sept 2016, USA
    Sum-of-squares Algorithms for Over-complete Tensor Decomposition
    Stanford theory seminar, Sept 2016, Stanford, USA
    IAS CSDM seminar, Mar 2016, Princeton, USA
    Gradient Descent Learns Linear Dynamical Systems
    IMA workshop, May 2016, Minneapolis, USA
    Communication Lower Bounds For Statistical Estimation Problems via a Distributed Data Processing Inequality
    STOC, Jun 2016, Boston, USA
    Invited talk at CISS, Mar 2016, Princeton, USA
    The Linear Algebraic Structure of Word Meanings
    UW Theory seminar, Apr 2016, Madison, USA
    MSR Talk Series, Nov 2015, Redmond, USA
    Analyzing Non-convex Optimization for Dictionary Learning
    ICML, July 2015, Lille, France
    MSR Redmond, Nev 2014, Redmond, USA
    Dagstuhl Seminar, Sep 2014, Dagstuhl, Germany
    On Communication Cost of Distributed Statistical Estimation and Dimensionality
    NIPS, Dec 2014, Montreal, Canada
    Provable Bounds for Learning Some Deep Representations
    ICML, Jun 2014, Beijing, China
    Columbia theory lunch, Feb 2014, NYC, USA
    CMU theory lunch, Feb 2014, Pittsburgh, USA
    Simulate Greedy Algorithms for Several Submodular Matroid Secretary Problems
    30th Symposium on Theoretical Aspects of Computer Science(STACS), Kiel, Germany, Feb 2013
    A New Variation of Hat Guessing Games
    17th International Computing and Combinatorics Conference(COCOON), Dallas, Texas, Aug 2011
    PC committees: ITCS 2018
    Journal refereeing: Journal of Machine Learning Research, Mathematics of Operations Research, IEEE Transaction on Information Theory, Optimization Methods and Software, Theoretical Computer Science, Transactions on Pattern Analysis and Machine Intelligence
    Conference refereeing: STOC, FOCS, ICML (with outstanding reviewer award in 2016), NIPS, COLT, AAAI(PC member), SODA, ISSAC