Qihang Lin Curriculum Vitae ___________________________________________________________________________________________ C

Qihang Lin
Curriculum Vitae
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Tippie College of Business
Phone: (412)294-2941
CONTACT
INFORMATION
RESEARCH
INTERESTS
EDUCATION
EXPERIENCE
PUBLICATIONS
AND WORKING
PAPERS
University of Iowa
21 East Market Street
Iowa City, IA, 52245
Email: [email protected]
Web: myweb.uiowa.edu/qihlin/index.html
Machine Learning
Stochastic Optimization
Convex Optimization
Algorithmic Crowdsourcing
Carnegie Mellon University, Pittsburgh, PA
Ph.D., Industrial Administration (Algorithms, Combinatorics and
Optimization), Tepper School of Business
Advisor: Javier Peña
Dissertation title: Large-Scale Optimization for Machine Learning
and Sequential Decision Making.
Tsinghua University, Beijing, China
B.S., Mathematical Science
Assistant Professor, Department of Management Science,
The University of Iowa, Iowa City, IA
Research Intern, Microsoft Research, Redmond, WA,
Research Intern, Microsoft Research, Beijing, China,
2008-2013
2004-2008
7/2013-present
5/2012-8/2012
10/2007-2/2008
Qihang Lin, Zhaosong Lu and Lin Xiao. An Accelerated Proximal Coordinate
Gradient Method and its Application to Regularzied Emprical Risk
Minimization. SIAM Journal on Optimization, Volume 25, 2015, 2244-2273.
Tianbao Yang, Rong Jin, Shenghuo Zhu, Qihang Lin. On Data Preconditioning for
Regularized Loss Minimization. Machine Learning, 2015, 1-23.
Qihang Lin, Xi Chen and Javier Peña. A Trade Execution Model under a Composite
Dynamic Coherent Risk Measure. Operations Research Letters. Volume 43, 2015,
52-58. This paper won the Best Student Paper Award in Financial Service Section of
INFORMS, 2012.
Qihang Lin and Lin Xiao. An Adaptive Accelerated Proximal Gradient Method
and its Homotopy Continuation for Sparse Optimization. Computational
Optimization and Applications, Volume 60, 2015, 633-674.
Xi Chen, Qihang Lin and Dengyong Zhou. Statistical Decision Making for Optimal
Budget Allocation in Crowd Labelling. Journal of Machine Learning Research,
Volume 16, 2015, 1-46.
Qihang Lin, Zhaosong Lu and Lin Xiao. An Accelerated Proximal Coordinate
Gradient Method. Advances in Neural Information Processing Systems (NIPS), 2014.
Qihang Lin and Lin Xiao. An Adaptive Accelerated Proximal Gradient Method
and its Homotopy Continuation for Sparse Optimization. International
Conference of Machine Learning (ICML), 2014.
Qihang Lin, Xi Chen and Javier Peña. A Sparsity Preserving Stochastic Gradient
Method for Composite Optimization. Computational Optimization and Application,
Volume 58 Issue 2 (2014), 455-482.
Qihang Lin, Xi Chen and Javier Peña. A Smoothing Stochastic Gradient Method for
Composite Optimization. Optimization Methods and Software, Volume 29, Issue 6
(2014), 1281-1301.
Qihang Lin, Xi Chen and Dengyong Zhou. Optimistic Knowledge Gradient Policy
for Optimal Budget Allocation in Crowdsourcing. International Conference of
Machine Learning (ICML), 2013.
Xi Chen, Qihang Lin and Javier Peña. Optimal Regularized Dual Averaging
Methods for Stochastic Optimization. Advances in Neural Information Processing
Systems (NIPS), 2012.
Xi Chen, Qihang Lin, Seyoung Kim, Jaime Carbonell and Eric P. Xing. Smoothing
Proximal Gradient Methods for General Structured Sparse Learning.
Annals of Applied Statistics, Volume 6, Number 2 (2012), 719-752.
Conference version is accepted in Uncertainty in Artificial Intelligence (UAI), 2011.
Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime Carbonell. Sparse Latent Semantic
Analysis. SIAM International Conference on Data Mining (SDM), 2011.
Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime Carbonell. Learning Preferences
using Millions of Parameters by Enforcing Sparsity. IEEE International
Conference on Data Mining (ICDM), 2010.
Adams Wei Yu, Qihang Lin, Tianbao Yang. Doubly Stochastic Primal-Dual
Coordinate Method for Regularized Empirical Risk Minimization with
Factorized Data. arXiv:1508.03390, Technical Report
Jason Lee, Qihang Lin, Tengyu Ma, Tianbao Yang. Distributed Stochastic Variance
Reduced Gradient Methods and A Lower Bound for Communication
Complexity. arXiv:1507.07595, Submitted.
Tianbao Yang, Lijun Zhang, Qihang Lin, Rong Jin. Fast Sparse Least-Squares
Regression with Non-Asymptotic Guarantees. arXiv:1507.0518, Technical Report
Xi Chen, Qihang Lin, Bodhisattva Sen. On Degrees of Freedom of Projection
Estimators with Applications to Multivariate Shape Restricted Regression.
arXiv:1509.01877, Submitted.
Tianbao Yang, Qihang Lin. Restarted SGD: Beating SGD without Smoothness
and/or Strong Convexity. arXiv:1512.03107, Technical Report.
Tianbao Yang, Qihang Lin. Stochastic subGradient Methods with Linear
Convergence for Polyhedral Convex Optimization. arXiv: 1510.01444, Technical
TEACHING
EXPERIENCE
Report.
Business Analytics (MBA, Spring 2014; BAC, Fall 2014, the University of Iowa);
Advanced Analytics (MBA, Fall 2013, Fall 2014, Fall 2015; BAC, Spring 2015, Spring
2016, the University of Iowa)
Text Analytics (MBA/BAC, Fall 2015, the University of Iowa)
Logistics and Supply Chain Management (Business Undergraduate, Spring 2013,
Carnegie Mellon University)
Mathematical Models for Consulting (Business Undergraduate, Summer
HONORS AND
AWARDS
2011, Carnegie Mellon University);
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Summer Research Award, Tippie College of Business
Old Gold Summer Fellowship, Tippie College of Business
2015
2014
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PRESENTATIONS
INFORMS Financial Services Section Best Student Research
Paper Competition, First Place.
Graduate Student Conference Funding, Carnegie Mellon
University
William Larimer Mellon Scholarship, Carnegie Mellon
University
Best Graduates Award, Tsinghua University, China
2012
2010-2012
2008-2011
2008
Bayesian Decision Process for Cost-Efficient Dynamic Ranking by Crowdsourcing.
INFORMS Annual Meeting, Philadelphia, PA, November 2015.
Optimal Budget Allocation for Online Crowdsourcing. Information and Decision
Sciences Seminar, University of Illinois at Chicago, September 2015.
Bayesian Decision Process for Cost-Efficient Dynamic Ranking by Crowdsourcing.
Computer Science Colloquium, The University of Iowa, October 2015.
Distributed Stochastic Variance Reduced Gradient Methods. The 15th Annual MOPTA,
Bethlehem, PA, July 2015.
Doubly Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk
Minimization with Factorized Data. The 22nd International Symposium on
Mathematical Programming. Pittsburgh, PA, July 2015.
Big Data Analytics: Optimization and Randomization, Proceedings of the 21th ACM
SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney
Australia, August 2015.
An Accelerated Proximal Coordinate Gradient Method and its Application to
Regularized Empirical Risk Minimization, Statistics Department Seminar,
The University of Iowa, April, 2015
An Accelerated Proximal Coordinate Gradient Method and its Application to
Regularized Empirical Risk Minimization, INFORMS Annual Meeting, San Francisco,
CA, November 2014.
An Accelerated Proximal Coordinate Gradient Method and its Application to
Regularized Empirical Risk Minimization, The 14th Annual MOPTA, Bethlehem, PA,
August 2014.
Accelerated Proximal-Gradient Homotopy Method for the Sparse Least-Squares,
International Conference of Machine Learning, Beijing, China, July 2014.
Accelerated Proximal-Gradient Homotopy Method for the Sparse Least-Squares,
SIAM Conference on Optimization, San Diego, CA, May 2014.
Optimal Trade Execution with Coherent Dynamic Risk Measures using Limit Orders,
American Mathematical Society Sectional Meetings, Albuquerque, NM, April 2014.
Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in
Crowdsourcing, The Applied Mathematical and Computational Sciences Seminar,
The University of Iowa, Iowa City, IA, February 2014.
Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in
Crowdsourcing, Seminar of Computer Science Department, Computer Science
Department, The University of Iowa, Iowa City, IA, November 2013.
Optimal Trade Execution with Coherent Dynamic Risk Measures using Limit Orders,
INFORMS Annual Meeting, Minneapolis, MN, USA, October 2013.
Optimal Trade Execution with Coherent Dynamic Risk Measures using Limit Orders,
The 5th Annual Modeling High Frequency Data in Finance Conference,
Hoboken, NJ, October 2013.
Optimistic Knowledge Gradient Policy for Budget Allocation in Crowdsourcing,
International Conference of Machine Learning, Atlanta, GA, USA, June 2013.
Optimization for Big Data Analysis: Complexity and Scalability, Tippie College of
Business, University of Iowa, Iowa City, IA, USA, February 2013
Optimistic Knowledge Gradient Policy for Budget Allocation in Crowdsourcing,
INFORMS Computing Society Conference, Santa Fe, NM, USA, January 2013.
Accelerated Proximal-Gradient Homotopy Method for the Sparse Least-Squares,
INFORMS Annual Meeting, Phoenix, AZ, USA, October 2012.
Optimal Trade Execution with Coherent Dynamic Risk Measures, INFORMS Annual
Meeting, Phoenix, AZ, USA, October 2012.
Accelerated Proximal-Gradient Homotopy Method for the Sparse Least-Squares,
Microsoft Research, Redmond, WA, USA, August 2012.
Optimal Trade Execution with Coherent Dynamic Risk Measures, The 12th Annual
MOPTA, Bethlehem, PA, USA, August 2012
Optimal Trade Execution with Coherent Dynamic Risk Measures, 21st International
Symposium on Mathematical Programming (ISMP), Berlin, Germany, August 2012.
Optimal Trade Execution with Coherent Dynamic Risk Measures, SIAM Conference on
Financial Mathematics and Engineering, Minneapolis, MN, USA, July 2012.
A Sparsity Preserving Stochastic Gradient Method for Composite Optimization,
INFORMS Annual Meeting, Charlotte, NC, USA, November 2011.
Optimal Trade Execution with Coherent Dynamic Risk Measures, Industrial-Academic
Workshop on Optimization in Finance and Risk Management Toronto, Canada,
October 2011.
A Sparsity Preserving Stochastic Gradient Method for Composite Optimization,
The 11th Annual MOPTA, Bethlehem, PA, USA, August 2011.
A Sparsity Preserving Stochastic Gradient Method for Composite Optimization, SIAM
COMPUTERS
SKILLS
PHD
COMMITTEES
REFEREE
Conference on Optimization, Darmstadt, Germany, May 2011
C/C++, Python, R, MATLAB, JMP, Hadoop, Linux, VBA
Senay Yasar Saglam, 2015, Management Sciences Department, The University of
Iowa
Xi Chen, 2016(expected), Management Sciences Department, The University of Iowa
Huan Jin, 2016(expected), Management Sciences Department, The University of
Iowa
Myung Cho, 2018(expected), Electrical and Computer Engineering Department, The
University of Iowa
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SIAM Journal on Optimization
6 papers
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PROFESSIONAL
SERVICES
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MEMBERSHIPS
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Operations Research
3 papers
Neural Computation
1 paper
Journal of Machine Learning Research
Mathematical Programming
ACM Transactions on Intelligent Systems and Technology
Information Systems Research
Computational Optimization and Applications
Annals of Operations Research
IEEE Transactions on Pattern Analysis and Machine
Intelligence
Co-Organizer of ICML ’13 Workshop: Machine
Learning Meets Crowdsourcing, Atlanta, GA.
Organization Committee Member of Master Program
in Business Analytics, The University of Iowa.
Faculty Search Committee Member, Management
Sciences Department, The University of Iowa
Program Committee Member for the 2015
Uncertainty in AI Conference (UAI), Amsterdam,
The Netherlands.
2 paper
1 papers
1 paper
1 paper
1 paper
1 paper
1 paper
June, 2013
2014-current
2015
2015
Institute For Operations Research and the Management Sciences (INFORMS)
Society for Industrial and Applied Mathematics (SIAM)
Mathematical Optimization Society (MOS)