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

With a wide range of applications, stochastic matching problems have been studied in
different models, including prophet inequality, Query-Commit, and Price-of-Information …

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

We study how to utilize (possibly erroneous) predictions in a model for computing under
uncertainty in which an algorithm can query unknown data. Our aim is to minimize the …

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 …

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 …

We introduce a novel adversarial model for scheduling with explorable uncertainty. In this
model, the processing time of a job can potentially be reduced (by an a priori unknown …

Pandora's Box is a central problem in decision making under uncertainty that can model
various real life scenarios. In this problem we are given n boxes, each with a fixed opening …

This paper presents a model of choice with two stages of information acquisition. In this
model, the choice problem can be interpreted as a variant of a more general multiarmed …

Given a hypergraph with uncertain node weights following known probability distributions,
we study the problem of querying as few nodes as possible until the identity of a node with …