We will survey recent work in the design of approximation algorithms for several discrete stochastic optimization problems, with a particular focus on 2-stage problems with recourse. In each of the ...

Geometric Optimization and Approximation Algorithms Publication Trend The graph below shows the total number of publications each year in Geometric Optimization and Approximation Algorithms.

In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs).

We consider an optimization problem for a dynamical system whose evolution depends on a collection of binary decision variables. We develop scalable approximation algorithms with provable ...

We design new approximation algorithms for the problems of optimizing submodular and supermodular functions subject to a single matroid constraint. Specifically, we consider the case in which we wish ...

In this talk we will present approximation algorithms (and general techniques) for some basic problems in the field of stochastic optimization. A canonical problem is stochastic knapsack: we are given ...

Introduction The Traveling Salesman Problem (TSP) is a well-known problem in optimization, where the objective is to find the shortest route to visit all cities and return to the starting point. This ...