Constrained submodular maximization problems encompass a wide variety of applications,
including personalized recommendation, team formation, and revenue maximization via …

Background. Our results tie into the literature on contention resolution schemes [3], which we
briefly define. Let P (𝐺) denote the fractional matching polytope of a graph 𝐺=(𝑉, 𝐸). In a …

Consider a network design application where we wish to lay down a minimum-cost
spanning tree in a given graph; however, we only have stochastic information about the …

Our main contribution is a general framework to design efficient polynomial time
approximation schemes (EPTAS) for fundamental stochastic combinatorial optimization …

Abstract The Prophet Inequality and Pandora's Box problems are fundamental stochastic
problem with applications in Mechanism Design, Online Algorithms, Stochastic Optimization …

Adaptive sequential decision making is one of the central challenges in machine learning
and artificial intelligence. In such problems, the goal is to design an interactive policy that …

The Pandora's Box problem and its extensions capture optimization problems with
stochastic input where the algorithm can obtain instantiations of input random variables at …

Martin Weitzman's" Pandora's problem" furnishes the mathematical basis for optimal search
theory in economics. Nearly 40 years later, Laura Doval introduced a version of the problem …

Two central problems in Stochastic Optimization are Min-Sum Set Cover and Pandora's Box.
In Pandora's Box, we are presented with n boxes, each containing an unknown value and …

The Pandora's Box Problem, originally formalized by Weitzman in 1979, models selection
from a set of options each with stochastic parameters, when evaluation (ie sampling) is …