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Concept

Wald's maximin model

Publications associées (5)

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Volkan Cevher

Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

2023

Relatively Robust Decisions

Thomas Alois Weber

It is natural for humans to judge the outcome of a decision under uncertainty as a percentage of an ex-post optimal performance. We propose a robust decision-making framework based on a relative performance index. It is shown that if the decision maker’s p ...

2023

A Catalyst Framework for Minimax Optimization

Negar Kiyavash

We introduce a generic two-loop scheme for smooth minimax optimization with strongly-convex-concave objectives. Our approach applies the accelerated proximal point framework (or Catalyst) to the associated dual problem and takes full advantage of existing ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2020

Incentivizing Truthful Responses with the Logarithmic Peer Truth Serum

Boi Faltings, Goran Radanovic

We consider a participatory sensing scenario where a group of private sensors observes the same phenomenon, such as air pollution. We design a novel payment mechanism that incentivizes participation and honest behavior using the peer prediction approach, i ...

2015

Incentive Schemes for Participatory Sensing

Boi Faltings, Goran Radanovic

We consider a participatory sensing scenario where a group of private sensors observes the same phenomenon, such as air pollution. Since sensors need to be installed and maintained, owners of sensors are inclined to provide inaccurate or random data. We de ...

2015