Speaker: Adam Diamand Abstract: We investigate the scheduling practices of multistage outpatient health programs that offer care plans customized to the needs of their patients. We formulate the scheduling problem as a Markov decision process (MDP) where patients can reschedule their appointment, may fail to show up, and may even become ineligible. The MDP has […]

Speaker: Saeed Ghadimi, Princeton University Abstract In this talk, we propose and analyze derivative-free stochastic approximation algorithms for nonconvex optimization. We first propose generalization of the conditional gradient algorithm achieving a similar rate to the standard stochastic gradient algorithm (SGD) using only noisy function evaluations (zeroth-order information). For the high-dimensional setting, we explore the advantage […]

Adam Elmachtoub, Columbia University Many real-world analytics problems involve two significant challenges: prediction and optimization. Due to the typically complex nature of each challenge, the standard paradigm is predict-then-optimize. By and large, machine learning tools are intended to minimize prediction error and do not account for how the predictions will be used in the downstream […]

Amin Khademi, Clemson University Abstract Identifying the right dose is one the most important decisions in drug development. Significant evidence has recently become available that emphasizes the role of patient covariates in optimal dose, i.e., a dose that is optimal for a patient group may be harmful for others. A key step towards personalized (precision) […]

Antoine Deza (McMaster University) Abstract The simplex and interior point methods are currently the most computationally successful algorithms for linear optimization. While the simplex methods follow an edge path, the interior point methods follow the central path. The algorithmic issues are closely related to the combinatorial and geometric structure of the feasible region. Focusing on the analysis […]

Speaker: Gustavo Angulo, Pontificia Universidad Católica de Chile Date/Time: August 20, 2019, 12:00pm-1:00pm Location: Bahen Centre, Room 1240 Abstract: The lexicographic order can be used to force a collection of decision vectors to be all different, i.e., to take on different values in some coordinates. We consider the set of fixed-size matrices with bounded integer […]

Speaker: Haoxiang Yang, Center for Nonlinear Studies, Los Alamos National Laboratory Date/Time: August 13, 2019, 12:00pm-1:00pm Location: Bahen Centre, Room 1220 Abstract: A stochastic disruption is a type of infrequent event in which the timing and the magnitude are random. We introduce the concept of stochastic disruptions and a stochastic optimization framework is proposed for […]