output
20122025
most citedDeep Learning for Physical Processes: Incorporating Prior Scientific Knowledge

259 citations

Showing cs.GTShow all

16 papers · 1 filter

cs.GT2024

Learning in Games with Progressive Hiding

Benjamin Heymann, Marc Lanctot

When learning to play an imperfect information game, it is often easier to first start with the basic mechanics of the game rules. For example, one can play several example rounds…

cs.GT2024

A pragmatic policy learning approach to account for users' fatigue in repeated auctions

Benjamin Heymann, Rémi Chan--Renous-Legoubin, Alexandre Gilotte

Online advertising banners are sold in real-time through auctions.Typically, the more banners a user is shown, the smaller the marginalvalue of the next banner for this user is. Th…

cs.GT2024

Feature-Based Online Bilateral Trade

Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni +2

Bilateral trade models the problem of facilitating trades between a seller and a buyer having private valuations for the item being sold. In the online version of the problem, the…

cs.GT2023

Local and adaptive mirror descents in extensive-form games

Côme Fiegel, Pierre Ménard, Tadashi Kozuno +3

We study how to learn -optimal strategies in zero-sum imperfect information games (IIG) with trajectory feedback. In this setting, players update their policies sequentially bas…

cs.GT2023

Addressing Bias in Online Selection with Limited Budget of Comparisons

Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder +1

Consider a hiring process with candidates coming from different universities. It is easy to order candidates with the same background, yet it can be challenging to compare them oth…

cs.GT2021★ 1 cited

A heuristic for estimating Nash equilibria in first-price auctions with correlated values

Benjamin Heymann, Panayotis Mertikopoulos

Our paper concerns the computation of Nash equilibria of first-price auctions with correlated values. While there exist several equilibrium computation methods for auctions with in…