4 citations · 5 across the 9 of their papers we have counts for
7 papers · 1 filter
Optimal Online Stochastic Matching
Paul Duetting, Michal Feldman, Mathieu Molina
We resolve the problem of unweighted online stochastic matching with a known arrival law by establishing its optimal competitive ratio. For Poisson arrivals, we achieve $1-e/e^e\ap…
Near-Optimal Acceleration for Smooth / Nondual Convex First-Order Oracle Optimization
David Martínez-Rubio, Brian Bullins, Cristóbal Guzmán +1
We study the optimization of convex objectives with -Hölder-continuous gradients in over , . (MG26) provides selectors with a movement bound fo…
Fair Prophets
Paul Duetting, Michal Feldman, Mathieu Molina
We initiate the study of -fair prophet inequalities. This interpolates between utilitarian welfare , Nash welfare , and Rawlsian max-min fairness . G…
The First-Order Oracle Complexity of Lipschitz Convex Optimization in Nondual Settings
David Martínez-Rubio, Brian Bullins, Cristóbal Guzmán +1
We study first-order black-box convex optimization over an -ball for objectives Lipschitz in the -norm, solving in the affirmative the nonsmooth version of the COLT…
Kernel Methods for Refined Prophet Inequalities
Patrick Loiseau, Mathieu Molina, Vianney Perchet +2
The single-selection prophet inequality is a canonical Bayesian online selection problem in which independent nonnegative values arrive sequentially and the decision-maker must irr…
Prophet Inequalities under Local Differential Privacy
Achraf Azize, Mathieu Molina, Hugo Richard +1
Many online decision platforms, from hiring marketplaces to auctions, face a tension between efficient decision-making and the protection of participants' privacy. Personal informa…
Tight Sample Complexity for Low-Degree and Sparse Boolean Polynomials
Jasper van Doornmalen, Mathieu Molina, Victor Verdugo +1
Motivated by the optimization of bounded binary black-box functions, we study the problem of learning polynomial surrogates over the Boolean hypercube. To ensure that optimizing th…