Information Complexity of Mixed-Integer Convex Optimization

Explore the information complexity of mixed-integer convex optimization in this distinguished seminar featuring Amitabh Basu from Johns Hopkins University. Delve into the challenges of minimizing convex functions under convex constraints with integer variables, focusing on the minimum number of oracle calls required for problem-solving. Discover nearly tight upper and lower bounds that extend classical results from continuous convex optimization. Gain insights into the study of information complexity under oracles revealing partial first-order information, and understand how these oracles compare to full first-order oracles in optimization efficiency. Learn about Professor Basu's background in mathematical optimization, his research interests, and his contributions to the field. Engage with open questions presented at the conclusion of this hour-long talk, which offers valuable knowledge for those interested in optimization techniques and data science.

Distinguished Seminar In Optimization and Data: Amitabh Basu (Johns Hopkins University)