Search Results for author: Michael Dinitz

Found 5 papers, 1 papers with code

Algorithms with Prediction Portfolios

1 code implementation22 Oct 2022 Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii

For each of these problems we introduce new algorithms that take advantage of multiple predictors, and prove bounds on the resulting performance.

Scheduling

Policy Regret in Repeated Games

no code implementations NeurIPS 2018 Raman Arora, Michael Dinitz, Teodor V. Marinov, Mehryar Mohri

We revisit the notion of policy regret and first show that there are online learning settings in which policy regret and external regret are incompatible: any sequence of play that achieves a favorable regret with respect to one definition must do poorly with respect to the other.

Fair Disaster Containment via Graph-Cut Problems

no code implementations9 Jun 2021 Michael Dinitz, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti

Graph cut problems are fundamental in Combinatorial Optimization, and are a central object of study in both theory and practice.

Combinatorial Optimization Fairness

Faster Matchings via Learned Duals

no code implementations NeurIPS 2021 Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii

Second, once the duals are feasible, they may not be optimal, so we show that they can be used to quickly find an optimal solution.

Combinatorial Optimization

Controlling Epidemic Spread using Probabilistic Diffusion Models on Networks

no code implementations16 Feb 2022 Amy Babay, Michael Dinitz, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti

The second is a Sample Average Approximation (SAA) based algorithm, which we analyze for the Chung-Lu random graph model.

Epidemiology

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