Yingyu Liang

UW-Madison

About Me

    2017-present



    2015-2017


    2014-2015


    2014


    Contact



    Research

  • Assistant Professor in Computer Sciences, University of Wisconsin-Madison
    I'm looking for motivated students who like research in Machine Learning! Contact me if you're interested.

  • Lecturer/Associate Research Scholar in Computer Science, Princeton University
    Host: Sanjeev Arora

  • Postdoc in Computer Science, Princeton University
    Hosts: Sanjeev Arora, Moses Charikar

  • Ph.D. in Computer Science, Georgia Tech
    Advisor: Maria-Florina Balcan

  • yliang at cs dot wisc dot edu
    Office 6393, Department of Computer Sciences, University of Wisconsin-Madison


  • Machine learning. In particular, providing theoretical foundations for modern machine learning models such as generalization bounds and provable non-convex optimization, designing efficient algorithms for real world applications such as those for natural languages and images.

Teaching

Publications

(authors are listed in alphabetic order, except for those papers with *)

Journal Publications

  • Mapping Between Natural Movie fMRI Responses and Word-Sequence Representations*
    Kiran Vodrahalli, Po-Hsuan Chen, Yingyu Liang, Janice Chen, Esther Yong, Christopher Honey, Peter Ramadge, Ken Norman, Sanjeev Arora.
    Neuroimage, 2017.
    [Neuroimage] [ARXIV][Appear in NIPS'16 Workshop]

  • Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks*
    Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song.
    To appear in Journal of Machine Learning Research (JMLR), 2017.
    [ARXIV] [CODE]

  • A Latent Variable Model Approach to PMI-based Word Embeddings
    Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, Andrej Risteski.
    Transactions of the Association for Computational Linguistics (TACL), 2016.
    [TACL] [ARXIV] [CODE] [Sanjeev's post]

  • Clustering Under Perturbation Resilience
    Maria-Florina Balcan, Yingyu Liang.
    SIAM Journal on Computing (SICOMP), 2016.
    [SICOMP] [ARXIV]

  • Robust Hierarchical Clustering
    Maria-Florina Balcan, Pramod Gupta, Yingyu Liang.
    Journal of Machine Learning Research (JMLR), 2014.
    [ARXIV] [CODE]

Manuscripts

  • Linear Algebraic Structure of Word Senses, with Applications to Polysemy
    Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, Andrej Risteski.
    [ARXIV] [CODE] [Sanjeev's post]

  • Why are Deep Nets Reversible: A Simple Theory, with Implications for Training
    Sanjeev Arora, Yingyu Liang, Tengyu Ma.
    [ARXIV][Appear in ICLR'16 Workshop]

Conference Publications

  • Generalization and Equilibrium in Generative Adversarial Nets (GANs)
    Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, Yi Zhang.
    International Conference on Machine Learning (ICML), 2017.
    [PAPER] [ARXIV]

  • Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations
    Yuanzhi Li, Yingyu Liang.
    International Conference on Machine Learning (ICML), 2017.
    [PAPER] [ARXIV] [CODE]

  • Differentially Private Clustering in High-Dimensional Euclidean Spaces
    Maria-Florina Balcan, Travis Dick, Yingyu Liang, Wenlong Mou, Hongyang Zhang.
    International Conference on Machine Learning (ICML), 2017.
    [PAPER]

  • A Simple but Tough-to-Beat Baseline for Sentence Embedding
    Sanjeev Arora, Yingyu Liang, Tengyu Ma.
    International Conference on Learning Representations (ICLR), 2017.
    [OPEN REVIEW] [CODE] [minimal example CODE] [Preliminary version appeared in NIPS'16 Workshop]

  • Diversity Leads to Generalization in Neural Networks*
    Bo Xie, Yingyu Liang, Le Song.
    International Conference on Artificial Intelligence and Statistics (AISTAT), 2017.
    [ARXIV][Preliminary version appeared in NIPS'16 Workshop]

  • Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates
    Yuanzhi Li, Yingyu Liang, Andrej Risteski.
    Neural Information Processing Systems (NIPS), 2016.
    [ARXIV]

  • Recovery Guarantee of Weighted Low-Rank Approximation via Alternating Minimization
    Yuanzhi Li, Yingyu Liang, Andrej Risteski.
    International Conference on Machine Learning (ICML), 2016.
    [ARXIV]

  • Communication Efficient Distributed Kernel Principal Component Analysis
    Maria-Florina Balcan, Yingyu Liang, Le Song, David Woodruff, Bo Xie.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016.
    [PAPER and VIDEO] [ARXIV]

  • Learning in Indefinite Proximity Spaces - Recent Trends*
    Frank-Michael Schleif, Peter Tino, Yingyu Liang.
    European Symposium on Artificial Neural Networks (ESANN), 2016.
    [PAPER]

  • Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients*
    Bo Xie, Yingyu Liang, Le Song.
    Neural Information Processing Systems (NIPS), 2015.
    [ARXIV]

  • Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning*
    Aurelien Bellet, Alireza Bagheri Garakani, Yingyu Liang, Maria-Florina Balcan, Fei Sha.
    SIAM International Conference on Data Mining (SDM), 2015.
    [ARXIV] [PRESENTATION] [CODE]

  • Scalable Kernel Methods via Doubly Stochastic Gradients*
    Bo Dai, Xie Dai, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song.
    Neural Information Processing Systems (NIPS), 2014.
    [ARXIV] [POSTER] [CODE]

  • Learning Time-Varying Coverage Functions*
    Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song.
    Neural Information Processing Systems (NIPS), 2014.
    [FULL VERSION] [POSTER]

  • Improved Distributed Principal Component Analysis
    Maria-Florina Balcan, Vandana Kanchanapally, Yingyu Liang, David Woodruff.
    Neural Information Processing Systems (NIPS), 2014.
    [ARXIV] [POSTER] [CODE]

  • Influence Function Learning in Information Diffusion Networks*
    Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song.
    The 31th International Conference on Machine Learning (ICML), 2014.
    [PAPER] [FULL VERSION] [POSTER] [CODE]

  • Distributed k-Means and k-Median Clustering on General Topologies
    Maria-Florina Balcan, Steven Ehrlich, Yingyu Liang.
    Neural Information Processing Systems (NIPS), 2013.
    [PAPER] [FULL VERSION] [SLIDES] [POSTER] [CODE]

  • Modeling and Detecting Community Hierarchies
    Maria-Florina Balcan, Yingyu Liang.
    The 2nd International Workshop on Similarity-Based Pattern Analysis and Recognition (SIMBAD), 2013.
    [PAPER] [SLIDES]

  • Efficient Semi-supervised and Active Learning of Disjunctions
    Maria-Florina Balcan, Christopher Berlind, Steven Ehrlich, Yingyu Liang.
    The 30th International Conference on Machine Learning (ICML), 2013.
    [PAPER] [SUPPLEMENTARY MATERIAL] [SPOTLIGHT] [POSTER]

  • Clustering under Perturbation Resilience
    Maria-Florina Balcan, Yingyu Liang.
    The 39th International Colloquium on Automata, Languages and Programming (ICALP), 2012.
    [PAPER] [SLIDES] [EXTENDED ARXIV VERSION] [POSTER]

  • Learning Vocabulary-based Hashing with AdaBoost*
    Yingyu Liang, Jianmin Li, Bo Zhang.
    The 16th International Conference of Multimedia Modeling (MMM), 2010.
    [PAPER]

  • Vocabulary-based Hashing for Image Search*
    Yingyu Liang, Jianmin Li, Bo Zhang.
    The ACM International Conference on Multimedia (MM), 2009.
    [PAPER]

Ph.D. Thesis

Machine Learning

Theoretical CS