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Hi. I'm Niao He

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I am an Assistant Professor in

Department of Industrial and Enterprise Systems Engineering,

University of Illinois at Urbana-Champaign

My research interest lies in developing fast algorithms and theoretical analysis for large-scale convex/stochastic/robust/distributed optimization with applications to finance, machine learning, and decision-making under uncertainty. I have a particular interest in the integration of optimization, machine learning and statistics.

Learn more about me

About Me

Complete CV upon request

B.S.

B.S. in Mathematics,
University of Science and Technology of China,
2006-2010

M.S.

M.S. in Computational Science&Engineering,
Gerogia Institute of Technology,
2014-2015

Ph.D.

Ph.D in Operational Research,
Advisor: Arkadi Nemirovski
Georgia Institute of Technology,
2010-2015  

Publications

Preprints
  1. Niao He, Zaid Harchaoui, Yichen Wang, and Le Song, "Fast and Simple Optimization for Poisson Likelihood models" , 2016
    [ arXiv:1608.01264]
Refereed Journals and Conference Publications
  1. Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, and Le Song, "Stochastic Generative Hashing" ,
    Proceedings of the 34th International Conference on Machine Learning (ICML), 2017
    [ arXiv:1701.02815]
  2. Bo Dai, Niao He, Yunpeng Pan, Byron Boots, and Le Song, "Learning from Conditional Distributions via Dual Kernel Embeddings" ,
    Artificial Intelligence and Statistics (AISTATS), 2017. [ arXiv:1607.04579]
  3. Bo Dai, Niao He, Hanjun Dai, and Le Song, "Provable Bayesian Inference via Particle Mirror Descent" ,
    Artificial Intelligence and Statistics (AISTATS), 2016 (Best Student Paper Award)
    [ arXiv:1506.03101][PDF]
  4. Nan Du, Yichen Wang, Niao He, and Le Song, "Time-Sensitive Recommendation From Recurrent User Activities" ,
    Neural Information Processing Systems (NIPS), 2015
    [ PDF ]
  5. Niao He, and Zaid Harchaoui, "Semi-proximal Mirror-Prox for Nonsmooth Composite Minimization" ,
    Neural Information Processing Systems (NIPS), 2015
    [ arXiv:1507.01476][ PDF ]
  6. Niao He, Anatoli Juditsky, and Arkadi Nemirovski, "Mirror Prox Algorithm for Multi-Term Composite Minimization and Semi-Separable Problems",
    Journal of Computational Optimization and Applications, 2015
    [arXiv:1311.1098][PDF]
  7. Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, and Le Song, "Scalable Kernel Methods via Doubly Stochastic Gradients",
    Neural Information Processing Systems (NIPS), 2014
    [arXiv:1407.5599][PDF]
  8. Hua Ouyang, Niao He, Long Tran, and Alexander Gray, "Stochastic Alternating Direction Method of Multipliers",
    Proceedings of the 30th International Conference on Machine Learning (ICML), 2013
    [arXiv:1211.0632][PDF]
Refereed Workshop Proceedings
  1. Niao He and Zaid Harchaoui, "Stochastic Semi-Proximal Mirror Prox",
    NIPS 8th Workshop on Optimization for Machine Learning, 2015
  2. Hua Ouyang, Niao He, and Alexander Gray, "Stochastic ADMM for Nonsmooth Optimization",
    NIPS 5th Workshop on Optimization for Machine Learning, 2012

Presentations

  1. Symposium on Frontiers in Big Data, September 2016
    University of Illinois at Urbana-Champaign
  2. ICCOPT on Optimization in Machine Learning, August 2016
    Tokyo, Japan
  3. INFORMS Optimization Society Conference on Optimiztion and Learning: New Problems, New Challenges, March 2016
    Princeton University, New Jersey
    Title: Convex and Stochastic Optimization Under Measurement Errors
  4. INFORMS Annual Meeting session on Trends in Optimization, November 2015
    Philadelphia, Pennsylvania
    Title: Convex and Stochastic Optimization Under Measurement Errors
  5. International Symposium on Mathematical Programming (ISMP), July 2015
    Pittsburgh, Pennsylvania
    Title: Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization
  6. IMA Workshop on Convexity and Optimization: Theory and Applications, February 2015
    University of Minnesota, Minneapolis, Minnesota
    Title: Recent Advances in Large-Scale Convex Optimization: Algorithms, Complexities, and Applications
  7. ISE Seminar, February 2015
    University of Illinois at Urbana-Champaign, Urbana, Illinois
    Title: Recent Advances in Large-Scale Convex Optimization: Algorithms, Complexities, and Applications
  8. LEAR Seminar, January 2015
    Microsoft-INRIA joint center, Grenoble, France
    Title: Some Recent Advances in Large-Scale Convex Optimization
  9. INFORMS Annual Meeting session on Recent Advances in First-Order Methods, November 2014
    San Francisco, California
    Title: Mirror Prox Algorithm for Multi-Term Composite Minimization
  10. Cornell ORIE Workshop on Data-Driven Decision Making, October 2014
    Cornell University, Ithaca, New York
    Title: Mirror Prox Algorithm for Multi-Term Composite Minimization
  11. INFORMS Optimization Society Conference on Theory and Practice: Dealing with Big Data and Other Challenges, March 2014
    Rice University, Houston, Texas
    Title: Mirror Prox Algorithm for Multi-Term Composite Minimization

Courses

Spring 2017
IE 521: Convex Optimization(graduate core, University of Illinois at Urbana-Champaign)

Fall 2016
IE 598: Big Data Optimization(graduate elective, University of Illinois at Urbana-Champaign)

Spring 2016
IE 300: Analysis of Data (undergraduate core, University of Illinois at Urbana-Champaign)

Spring 2015
ISyE 3770: Statistics and Applications (undergraduate core, Georgia Institute of Technology)

Email
niaohe AT illinois DOT edu

Office

Department of Industrial & Enterprise Systems Engineering
University of Illinois at Urbana-Champaign
117 Transportation Building
Urbana, Illinois 61801

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