Zobrazeno 1 - 10
of 13 222
pro vyhledávání: '"Gaillard, P"'
We address the online unconstrained submodular maximization problem (Online USM), in a setting with stochastic bandit feedback. In this framework, a decision-maker receives noisy rewards from a nonmonotone submodular function, taking values in a know
Externí odkaz:
http://arxiv.org/abs/2410.08578
We study boosting for adversarial online nonparametric regression with general convex losses. We first introduce a parameter-free online gradient boosting (OGB) algorithm and show that its application to chaining trees achieves minimax optimal regret
Externí odkaz:
http://arxiv.org/abs/2410.03363
Recent ethnographic research reveals that gang dynamics in Chicago's Southside have evolved with decentralized micro-gang "set" factions and cross-gang interpersonal networks marking the contemporary landscape. However, standard police datasets lack
Externí odkaz:
http://arxiv.org/abs/2408.10018
We study a theoretical and algorithmic framework for structured prediction in the online learning setting. The problem of structured prediction, i.e. estimating function where the output space lacks a vectorial structure, is well studied in the liter
Externí odkaz:
http://arxiv.org/abs/2406.12366
Autor:
Gaillard, A., Herrada, M. A., Deblais, A., van Poelgeest, C., Laruelle, L., Eggers, J., Bonn, D.
In this experimental and numerical study, we revisit the question of the onset of the elastic regime in viscoelastic pinch-off. This is relevant for all modern filament thinning techniques which aim at measuring the extensional properties of low-visc
Externí odkaz:
http://arxiv.org/abs/2406.02303
We explore online learning in episodic loop-free Markov decision processes on non-stationary environments (changing losses and probability transitions). Our focus is on the Concave Utility Reinforcement Learning problem (CURL), an extension of classi
Externí odkaz:
http://arxiv.org/abs/2405.19807
Time-to-event analysis is a branch of statistics that has increased in popularity during the last decades due to its many application fields, such as predictive maintenance, customer churn prediction and population lifetime estimation. In this paper,
Externí odkaz:
http://arxiv.org/abs/2403.07460
Autor:
Saha, Aadirupa, Gaillard, Pierre
We address the problem of active online assortment optimization problem with preference feedback, which is a framework for modeling user choices and subsetwise utility maximization. The framework is useful in various real-world applications including
Externí odkaz:
http://arxiv.org/abs/2402.18917
We address the problem of stochastic combinatorial semi-bandits, where a player selects among P actions from the power set of a set containing d base items. Adaptivity to the problem's structure is essential in order to obtain optimal regret upper bo
Externí odkaz:
http://arxiv.org/abs/2402.15171
Autor:
Gaillard, Louis, Din, Mohab Safey El
We consider systems of polynomial equations and inequalities in $\mathbb{Q}[\boldsymbol{y}][\boldsymbol{x}]$ where $\boldsymbol{x} = (x_1, \ldots, x_n)$ and $\boldsymbol{y} = (y_1, \ldots,y_t)$. The $\boldsymbol{y}$ indeterminates are considered as p
Externí odkaz:
http://arxiv.org/abs/2402.07782