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Publications associées (32)

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

Mathieu Salzmann, Alexandre Massoud Alahi, Megh Hiren Shukla

Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...

2024

Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units

Olga Fink, Mina Montazeri

This paper proposes a safe reinforcement learning algorithm for generation bidding decisions and unit maintenance scheduling in a competitive electricity market environment. In this problem, each unit aims to find a bidding strategy that maximizes its reve ...

ELSEVIER SCI LTD2023

The Role of Adaptivity in Source Identification with Time Queries

Gergely Odor

Understanding epidemic propagation in large networks is an important but challenging task, especially since we usually lack information, and the information that we have is often counter-intuitive. An illustrative example is the dependence of the final siz ...

EPFL2022

This paper tackles the problem of adversarial examples from a game theoretic point of view. We study the open question of the existence of mixed Nash equilibria in the zero-sum game formed by the attacker and the classifier. While previous works usually al ...

2021

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Motivated by applications in shared mobility, we address the problem of allocating a group of agents to a set of resources to maximize a cumulative welfare objective. We model the welfare obtainable from each resource as a monotone DR-submodular function w ...

PMLR2021

Suppose we have randomized decision trees for an outer function f and an inner function g. The natural approach for obtaining a randomized decision tree for the composed function (f∘ gⁿ)(x¹,…,xⁿ) = f(g(x¹),…,g(xⁿ)) involves amplifying the success probabili ...

Schloss Dagstuhl - Leibniz-Zentrum für Informatik2020

A Multiagent Model of Efficient and Sustainable Financial Markets

In this paper, we introduce a model of a financial market as a multiagent repeated game where the players are market makers. We formalize the concept of market making and the parameters of the game. Our main contribution is a framework that combines game t ...

2020

Adapting Governance Incentives to Avoid Common Pool Resource Underuse: The Case of Swiss Summer Pastures

Ivo Philippe Baur

The use of summer pastures in the European Alps provides much evidence against Hardin's prediction of the tragedy of the commons. For centuries, farmers have kept summer pastures in communal tenure and avoided its overuse with self-designed regulations. Du ...

2018

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To overcome the problem of outlier data in the regression analysis for numerical-based damage spectra, the C4.5 decision tree learning algorithm is used to predict damage in reinforced concrete buildings in future earthquake scenarios. Reinforced concrete ...

Elsevier2014

In this paper a 2-phase decision tree algorithm is developed to qualitatively predict damage in RC buildings based on earthquake characteristics and structural properties. To this end, the structural properties considered are the natural period of the fund ...

2013

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