[FYI: Colloquium, School of Computing]
Bridging Continuous and Discrete Optimization through the Lens of Approximation
Euiwoong Lee (이의웅)
Courant Institute of Mathematical Sciences, NYU, New York, USA
Courant Institute of Mathematical Sciences, NYU, New York, USA
2018/11/12 Mon 4PM (Bldg. E3-1, Room 1501)
Mathematical optimization is a field that studies algorithms, given an objective function and a feasible set, to find the element that maximizes or minimizes the objective function from the feasible set. While most interesting optimization problems are NP-hard and unlikely to admit efficient algorithms that find the exact optimal solution, many of them admit efficient “approximation algorithms” that find an approximate optimal solution.
Continuous and discrete optimization are the two main branches of mathematical optimization that have been primarily studied in different contexts. In this talk, I will introduce my recent results that bridge some of important continuous and discrete optimization problems, such as matrix low-rank approximation and Unique Games. At the heart of the connection is the problem of approximately computing the operator norm of a matrix with respect to various norms, which will allow us to borrow mathematical tools from functional analysis.
Continuous and discrete optimization are the two main branches of mathematical optimization that have been primarily studied in different contexts. In this talk, I will introduce my recent results that bridge some of important continuous and discrete optimization problems, such as matrix low-rank approximation and Unique Games. At the heart of the connection is the problem of approximately computing the operator norm of a matrix with respect to various norms, which will allow us to borrow mathematical tools from functional analysis.