Yingyu Liang

Georgia Tech, College of Computing

About Me [CV]

Aug 2010 -


2010

2008


Contact

  • Research Assistant, School of Computer Science, Georgia Tech
    Advisor: Maria-Florina Balcan

  • M. S. in Computer Science, Tsinghua University

  • B. S. in Computer Science, Tsinghua University


  • yliang39 AT gatech Dot edu

  • School of Computer Science, KACB 2116, Gatech, Atlanta 30332.

Research [STATEMENT]

My primary research interests are in machine learning theory and algorithms. The common thread in my research is the study of modern paradigms of machine learning, involving both the development of mathematical models and the design of efficient algorithms.

  • Distributed machine learning
  • Theoretical foundation of clustering
  • Efficient active and semi-supervised learning
  • Learning over networks

Publications

Manuscripts

  • Clustering Under Perturbation Resilience
    With Maria-Florina Balcan.
    [DRAFT](extended version with new algorithms and new results, especially new bounds on min-sum clustering)

  • Robust Hierarchical Clustering
    With Maria-Florina Balcan, Pramod Gupta.
    [ARXIV]

  • Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning
    With Aurelien Bellet, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha.

  • Fast and Communication Efficient Algorithms for Distributed PCA
    With David Woodruff, Maria-Florina Balcan, Vandana Kanchanapally.

  • Budgeted Influence Maximization for Multiple Products
    With Nan Du, Maria-Florina Balcan, Le Song.

Conference

  • Influence Function Learning in Information Diffusion Networks
    With Nan Du, Maria-Florina Balcan, Le Song.
    The 31th International Conference on Machine Learning (ICML 2014).

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

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

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

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

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

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

Workshop

  • Distributed PCA and k-Means Clustering
    With Maria-Florina Balcan, Vandana Kanchanapally.
    The Big Learning Workshop in NIPS 2013.
    [PAPER] [PRESENTATION] [POSTER] [CODE]

  • Clustering Perturbation Resilient k-Median Instances
    With Maria-Florina Balcan.
    The Learning Faster from Easy Data Workshop in NIPS 2013.
    [PAPER] [SPOTLIGHT] [POSTER]

  • THU-IMG at TRECVID 2009
    With Binbin Cao, Jianmin Li, Chenguang Zhu, Yongchao Zhang, Chenhao Tan, Ge Chen, Chen Sun, Jinhui Yuan, Mingxing Xu, Bo Zhang.
    The TRECVID workshop, 2009.
    [REPORT]

  • THU and ICRC at TRECVID 2008
    With Xiaobing Liu, Zhikun Wang, Jianmin Li, Binbin Cao, Zhichao Cao, Zhenlong Dai, Zhishan Guo, Wen Li, Leigang Luo, Zhaoshi Meng, Yinfeng Qin, Shi Qiu, Aibo Tian, Dong Wang, Qiuping Wang, Chenguang Zhu, Xiaolin Hu, Jinhui Yuan, Peijiang Yuan, Bo Zhang, Shi Chen, JianGuo Li, Tao Wang, Yimin Zhang.
    The TRECVID workshop, 2008.
    [REPORT]

  • THU and ICRC at TRECVID 2007
    With Jinhui Yuan, Zhishan Guo, Li Lv, Wei Wan, Teng Zhang, Dong Wang, Xiaobing Liu, Cailiang Liu, Shengqi Zhu, Duanpeng Wang, Yang Pang, Nan Ding, Ying Liu, Jiangping Wang, Xiujun Zhang, Xiaozheng Tie, Zhikun Wang, Huiyi Wang, Tongchun Xiao, Yinyu Liang, Jianmin Li, Fuzong Lin, Bo Zhang, JianGuo Li, WeiXin Wu, XiaoFeng Tong, DaYong Ding, YuRong Chen, Tao Wang, Yimin Zhang.
    The TRECVID workshop, 2007.
    [REPORT]

Thesis Proposal

Master Thesis

Activities

Presentations

  • Clustering under perturbation resilience

    • Learning Faster from Easy Data Workshop at NIPS, December 2013
    • University of Maryland, September 2013
    • ACO student seminar, Georgia Institute of Technology, August 2013
    • Theory group seminar, Georgia Institute of Technology, July 2012

  • Distributed PCA and k-means clustering

    • Georgia Scientific Computing Symposium, February 2014
    • Big Learning Workshop at NIPS, December 2013

  • Distributed k-median and k-means clustering on general topologies

    • NIPS, December 2013
    • HPArch Lab, Georgia Institute of Technology, November 2013
    • George Washington University, September 2013
    • MURI Symposium, University of Maryland, September 2013

  • Efficient semi-supervised and active learning of disjunctions

    • ICML, June 2013

Symposiums

  • Georgia Scientific Computing Symposium, February 2014

  • MURI Symposium, September 2013

  • ARC Theory Day, April 2013

  • ARC-Yandex Workshop: Internet Topology and Economics, November 2012

  • CMU Summer School on Algorithmic Economics, August 2012

  • Center of Data Analytics Workshop on Big Data Research and Development, April 2012

  • ARC Submodular Workshop, March 2012

  • ARC Theory Day, November 2011

  • Machine Learning Summer School at Purdue, June 2011

Service

  • Organizer of Machine Learning Reading Group at Georgia Tech, 2012-present

  • ICML 2013 Volunteer, June 2013

  • ICCI 2010 PC Member

  • Tsinghua University CS PhD Forum 2010 PC member

  • Reviewer for COLT 2012, UAI 2012, STACS 2013; Data Mining and Knowledge Discovery 2011, IEEE Transactions on Information Theory 2014

Machine Learning

Theoretical CS