ISE Seminar Calendar
http://illinois.edu/calendar/list/3605
Industrial and Enterprise Systems Engineering Seminars/SpeakersISE Seminar-"Sparse" Computation of Gradients for Optimization with Large Data Sets
http://illinois.edu/calendar/detail/3605/32126940
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/32126940Mon, 27 Oct 2014 16:00:00 CDTAbstractThe last few years have seen an increasing interest in utilizing optimization for large-scale data analysis. However, optimization problems arising from these applications often involve, in addition to expensive smooth components for data fitting, nonsmooth and nonseparable regularization terms to enforce certain structural properties for the generated solutions (e.g, low rank or group sparsity). It is well-known that such nonsmooth components can significantly slow down the convergence of existing first-order optimization algorithms, leading to a large number of traverses through the data sets. To address this issue, we present a new class of optimization techniques, referred as to gradient sliding and conditional gradient sliding methods, which can skip the computation of gradients from time to time while still maintaining the overall optimal rate of convergence. In particular, the number of gradient evaluations required for these algorithms will be the same as if the aforementioned nonsmooth and nonseparable components do not exist. When applied to data analysis problems, these algorithms can reduce the number of scans through the data set by orders of magnitude. Numerical experiments have been conducted to illustrate the effectiveness of these techniques.BiographyGuanghui (George) Lan obtained his Ph.D. degree in Industrial and Systems Engineering from Georgia Institute of Technology in August, 2009. He then joined the Department of Industrial and Systems Engineering at the University of Florida as an assistant professor thereafter. His main research interests lie in stochastic optimization, nonlinear programming, simulation-based optimization, and their applications in data analysis. His research has been supported by the National Science Foundation and Office of Naval Research. The academic honors that he received include the INFORMS Computing Society Student Paper Competition First Place (2008), INFORMS George Nicholson Paper Competition Second Place (2008), Mathematical Optimization Society Tucker Prize Finalist (2012), INFORMS Junior Faculty Interest Group (JFIG) Paper Competition First Place (2012) and the National Science Foundation CAREER Award (2013).ISE Seminar featuring-Dynamic Pricing and Inventroy Control with Nonparametric Demand Learning
http://illinois.edu/calendar/detail/3605/32033243
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/32033243Thu, 30 Oct 2014 16:00:00 CDTAbstractWe consider a retailer selling a single nonperishable product over a finite horizon. Demand is stochastic and price-dependent. At the beginning of each period, the firm determines its selling price and inventory replenishment decisions, but it knows neither the dependency of demand on selling price nor the distribution of demand uncertainty, hence it has to make pricing and ordering decisions only based on historical demand data. We propose a nonparametric data-driven policy that learns the demand-price relationship and the random error distribution on the fly. The policy integrates the phases of exploration and exploitation and converges to the true optimal solution. Besides convergence of optimal policies, we also establish the convergence rate of the regret, defined as the profit loss compared with that of the optimal solution when the firm had known the random demand information. This is joint work with Beryl Chen and Hyun-Soo Ahn.BiographyXiuli Chao is a professor of Industrial and Operations Engineering at the University of Michigan, Ann Arbor. His research interests include stochastic modeling and optimization, queueing, inventory control, and supply chain management. He is the co-author of two books, "Operations Scheduling with Applications in Manufacturing and Services" (Irwin/McGraw-Hill, 1998), and "Queueing Networks: Customers, Signals, and Product Form Solutions" (John Wiley & Sons, 1999). Chao received the 1998 Erlang Prize from the Applied Probability Society of INFORMS, and in 2005 he received the David F. Baker Distinguished Research Award from Institute of Industrial Engineers (IIE). He holds a doctoral degree in Operations Research from Columbia University.ISE Seminar featuring Milind Sohoni, Indian School of Business
http://illinois.edu/calendar/detail/3605/32033848
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/32033848Thu, 06 Nov 2014 16:00:00 CSTISE Seminar featuring Phil Smith, The Ohio State University
http://illinois.edu/calendar/detail/3605/31992977
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/31992977Thu, 13 Nov 2014 16:00:00 CSTISE Seminar featuring Janis Terpeny, Iowas State University
http://illinois.edu/calendar/detail/3605/31993096
GE/IE 590 Seminarhttp://illinois.edu/calendar/detail/3605/31993096Thu, 12 Feb 2015 16:00:00 CST