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Qihang Lin
Assistant Professor
Contact
319-335-0988
Office
S380 Pappajohn Business Building (PBB)
Academic history 
PhD in Operations Research, Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, 2013
BS in Mathematical Science, Tsinghua University, Beijing, China, 2008
Expertise 
Algorithmic Crowdsourcing
Convex Optimization
Machine Learning
Stochastic Optimization
Awards 
Summer Research Award, Tippie College of Business, The University of Iowa, 2015
Old Gold Summer Fellowship, Tippie College of Business, The University of Iowa, 2014
Best Student Paper Award , Financial Service Section of INFORMS, 2012
Selected publications 

An Accelerated Randomized Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization. Qihang Lin, Zhaosong Lu, Lin Xiao, SIAM Journal on Optimization, 2015, vol 25, 2244-2273

On Data Preconditioning for Regularized Loss Minimization. Tianbao Yang, Rong Jin, Shenghuo Zhu, Qihang Lin, Machine Learning, 2015, 1-23

A Trade Execution Model under a Composite Dynamic Coherent Risk Measure. Qihang Lin, Xi Chen, Javier Pena, Operations Research Letters, 2015, vol 43, 52–58

An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization. Qihang Lin, Lin Xiao, Computational Optimization and Applications, 2014, vol 60, 633-674

Statistical Decision Making for Optimal Budget Allocation in Crowd Labelling. Xi Chen, Qihang Lin, Dengyong Zhou, Journal of Machine Learning Research, 2014, vol 16, 1-46

A Smoothing Stochastic Gradient Method for Composite Optimization. Qihang Lin, Xi Chen, Javier Pena, Optimization Methods and Software, 2014, vol 29, 1281-1301

A Sparsity Preserving Stochastic Gradient Method for Composite Optimization. Qihang Lin, Xi Chen, Javier Pena, Computational Optimization and Applications, 2014, vol 58, 455-482

Smoothing Proximal Gradient Methods for General Structured Sparse Learning. Xi Chen, Qihang Lin, Seyoung Kim, Jaime Carbonell, Eric P. Xing, Annals of Applied Statistics, 2012, vol 6, 719-752

Sponsored research 

A Cost-Efficient Dynamic Crowdsourcing Strategy for Data Labeling: Rating, Ranking and Classification. Qihang Lin, Tippie College of Business, The University of Iowa

Conference proceedings 

Inverse SVM classication by nonconvex
optimization with budget and cost constraints. Mike T. Lash, Qihang Lin, Nick Street, Jennifer G. Robinson

An Accelerated Proximal Coordinate Gradient Method. Qihang Lin, Zhaosong Lu, Lin Xiao, Advances in Neural Information Processing Systems (NIPS), 2014

An Accelerated Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem. Qihang Lin, Lin Xiao, International Conference on Machine Learning (ICML), 2014

Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing. Qihang Lin, Xi Chen, Dengyong Zhou, International Conference on Machine Learning (ICML), 2013

Optimal Regularized Dual Averaging Methods for Stochastic Optimization. Xi Chen, Qihang Lin, Javier Pena, Advances in Neural Information Processing Systems (NIPS), 2012

Smoothing Proximal Gradient Method for General Structured Sparse Learning. Xi Chen, Qihang Lin, Seyoung Kim, Jaime Carbonell, Eric Xing, Uncertainty in Artificial Intelligence (UAI), 2011

Sparse Latent Semantic Analysis. Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime Carbonell, SIAM International Conference on Data Mining (SDM), 2011

Learning Preferences using Millions of Parameters by Enforcing Sparsity. Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime Carbonell, IEEE International Conference on Data Mining (ICDM), 2010

Current and prior positions 
Research Intern, Machine Learning Department, Microsoft Research, Redmond, WA, May 2012 - August 2012
Research Intern, Machine Learning Department, Microsoft Research, Bejing, China, October 2007 - February 2008
Review and editorial work 

Referee, Journal of Machine Learning Research , May 2015 - Current

Referee, Information Systems Research, September 2014 - Current

Referee, SIAM Journal on Optimization, May 2012 - Current

Referee, Mathematical Programming, April 2015 - November 2015

Referee, Operations Research, March 2013 - October 2015

Referee, Annals of Operations Research, February 2015 - August 2015

Referee, Neural Computation, January 2015 - May 2015

Referee, ACM Transactions on Intelligent Systems and Technology, December 2014 - April 2015

Referee, IEEE Transactions on Pattern Analysis and Machine Intelligence, May 2014 - December 2014

Referee, Computational Optimization and Applications, May 2014 - September 2014

Presentations 

Bayesian Decision Process for Cost-Efficient Dynamic Ranking by Crowdsourcing. INFORMS Annual Meeting, Philadelphia, PA, November 2015

Bayesian Decision Process for Cost-Efficient Dynamic Ranking by Crowdsourcing. Computer Science Colloquium, Iowa City, IA, October 2015

Optimal Budget Allocation for Online Crowdsourcing. Information Decision Science Department Seminar, Chicago, IL, September 2015

Big Data Analytics: Optimization and Randomization. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, Australia, August 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

An Accelerated Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization. Statistics Department Seminar, Iowa City, IA, April 2015

An Accelerated Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization. INFORMS Annual Meeting, San Francisco, CA, USA, November 2014

An Accelerated Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization. The 14th Annual MOPTA, Bethlehem, PA, USA, 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. Seminar: AMCS, Iowa City, IA, February 2014

Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing. Seminar of Computer Science Department, 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., 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., 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 2012), 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 Conference on Optimization, Darmstadt, Germany, May 2011

Committees and professional service 
Organization Committee of Master Program in Business Analytics, 2014 - Current
Faculty Search Committee, 2015
Co-Organizer of ICML ’13 Workshop: Machine Learning Meets Crowdsourcing, 2013