Event Category: Operations Research Seminar Series
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Boosted Second Price Auctions: Revenue Optimization for Heterogeneous Bidders
3/7/19 | 4:15pm | E51-335 Reception to follow. Negin Golrezaei Assistant Professor of Operation Management MIT Abstract: The second price auction has been the prevalent auction format used by advertising exchanges because of its simplicity and desirable incentive properties. However, even with an optimized choice of reserve prices, this auction is…
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Under the Hood of Bike Sharing
2/28/19 | 4:15pm | E51-335 Reception to follow. Shane Henderson Professor and Director School of Operations Research and Information Engineering Cornell University Abstract: Cornell’s work on bike sharing with Citi Bike and its parent company Motivate relies on a combination of data analysis, stochastic modeling and optimization to help inform both…
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Nonlinear Programming Formulations of Chance-Constraints
2/21/19 | 4:15pm | E51-335 Reception to follow. Andreas Wächter Associate Professor of Industrial Engineering and Management Sciences Northwestern University Abstract: We discuss a new approximation of chance constraints that results in differentiable functions which can be integrated in nonlinear optimization problems and solved with standard nonlinear programming techniques. For problems…
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Learning to Discover Drugs
2/14/19 | 4:15pm | E51-335 Reception to follow. Regina Barzilay Delta Electronics Professor MIT Abstract: Rapid developments in machine learning have completely transformed multiple areas of science and engineering. While today penetration of this technology into the pharmaceutical industry and medicine is still limited, the situation is rapidly changing. In this…
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Reducing Exploration in Personalized Decision-Making
11/15/18 | 4:15pm | E51-335 Reception to follow. Mohsen Bayati Associate Professor Stanford University Abstract: A central problem in personalized decision-making is to learn decision outcomes as functions of individual-specific covariates (contexts). Current literature on this topic focuses on algorithms that balance an exploration-exploitation tradeoff, to ensure sufficient rate of learning…
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Establishing Trust and Trustworthiness in Global Businesses
11/1/18 | 4:15pm | E51-335 Reception to follow. Ozalp Ozer Ashbel Smith Chair Professor of Management Science University of Texas Abstract: In this presentation, we will discuss when, how, and why the behavioral motives of trust and trustworthiness arise to support cooperation within and across businesses. We identify four building blocks…
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Building Analytic Applications in the Real World: Case Studies and Lessons from Retail and E-Commerce
10/25/18 | 4:15pm | E51-335 Reception to follow. Rama Ramakrishnan Entrepreneur Salesforce Abstract: Rama will share his experiences building analytic applications over the past 15 years. These applications were at the core of two successful technology startups focused on retail and e-commerce and are now part of the product portfolios of…
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From School Buses to Start Times: Driving Policy With Optimization
10/18/18 | 4:15pm | E51-335 Reception to follow. Arthur Delarue & Sebastien Martin PhD candidates MIT Abstract: Maintaining a fleet of buses to transport students to school is a major expense for U.S. school districts. In order to reduce transportation costs by allowing buses to be reused between schools, many districts…
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More Virtuous Smoothing for Global Optimization: Haunted by the Ghost of Rolle
10/11/18 | 4:15pm | E51-335 Reception to follow. Jon Lee G. Lawton and Louise G. Johnson Professor of Engineering University of Michigan Abstract: In the context of global optimization of mixed-integer nonlinear optimization (MINLO) formulations, we consider smoothing univariate concave increasing functions that have poorly behaved derivative at 0 (for example,…
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Out-Of-Sample Validation and Distributional Robustness
10/4/18 | 4:15pm | E51-335 Reception to follow. Bart Van Parys Assistant Professor MIT Abstract: This talk deals with the problem of overfitting in data-driven decision-making. Decisions based on one particular dataset indeed often have poor out-of-sample performance; a phenomenon commonly denoted as the “curse of optimization”. Distributional robust optimization has…