Talk Title: A superlinearly convergent first-order method for nonsmooth optimization Abstract: Nonsmooth optimization problems appear throughout machine learning and signal processing. However, standard first-order methods for nonsmooth optimization can be slow for "poorly conditioned" problems. In this talk, I will present a locally accelerated first-order method that is less sensitive to conditioning and achieves superlinear…

Talk Title Bridging Online and Offline Learning Towards Improved Data-Driven Operations Management Abstract Modern organizations’ operations require increasing use of machine learning tools. While supervised machine learning traditionally excels at making predictions based on i.i.d. offline data, many modern operational tasks require making sequential decisions based on data collected online. Bridging the gap between offline…

Talk Title: Provably Good Region Partitioning for On-Time Last-Mile Delivery Abstract: People expect faster delivery of goods ranging from groceries to medicines. Managing on-time delivery systems is challenging because of the underlying uncertainties and combinatorial nature of the routing decision. In practice, the efficiency of such systems also hinges on the driver's familiarity with the…

Talk Title Benefits of Randomization in First Order Algorithms for Min-Max Optimization Abstract Modern data science applications require solving high dimensional optimization problems with large number of data points. Min-max optimization provides a unified framework for many problems in this context ranging from empirical risk minimization and distributionally robust optimization in machine learning to medical…

Talk Title Optimal Rationing of Pooled Resources with Individual Service-Level Constraints Abstract Resource pooling is a fundamental concept in supply chain management for reducing and hedging uncertainty. An important problem in resource pooling is to decide (1) the capacity level of pooled resources in anticipation of random demand of multiple customers and (2) how the…

Talk Title: Theory and Algorithms for Non(-Clarke)-Regular Optimization Problems Abstract: Despite the growing interest in nonconvex and nonsmooth optimization problems among the continuous optimization community, much of the current research focuses on Clarke-regular objectives and constraints. This regularity leads to favorable computational properties, but limits the practical applicability of the algorithms developed. In this talk,…

Talk Title: Generalized Submodular Optimization—Theory, Algorithms, and Applications Abstract: Submodularity is an important concept in integer and combinatorial optimization. Submodular set functions capture diminishing returns, and for this desirable property, they are found in numerous real-world applications. A submodular set function models the effect of selecting items from a single ground set, and whether an…

Join Berkeley IEOR alum Anurag Aiyer (BS IEOR '22) and Visa recruiter Ilya Rosenblatt as they discuss internship opportunities available at Visa, as well as strategies to stand out as a candidate. This event will be catered. We ask that you RSVP by February 14. About Visa: Visa is a world leader in payments and…