Zobrazeno 1 - 10
of 8 630
pro vyhledávání: '"Maillard P"'
Publikováno v:
ESAIM: Proceedings and Surveys, Vol 74, Pp 137-157 (2023)
We collect recent results on random matrices and random graphs. The topics covered are: fluctuations of the empirical measure of random matrices, finite-size effects of algorithms involving random matrices, characteristic polynomial of sparse matrice
Externí odkaz:
https://doaj.org/article/b53f5402e382439bb01a09b5a3812172
In this paper, we study a discrete-time analogue of a Hawkes process, modelled as a Poisson autoregressive process whose parameters depend on the past of the trajectory. The model is characterized to allow these parameters to take negative values, mo
Externí odkaz:
http://arxiv.org/abs/2409.01660
Autor:
Dutto, Alessandro, Kan, Anton, Saraw, Zoubeir, Maillard, Aline, Zindel, Daniel, Studart, André R.
Microorganisms hosted in abiotic structures have led to engineered living materials that can grow, sense and adapt in ways that mimic biological systems. Although porous structures should favor colonization by microorganisms, they have not yet been e
Externí odkaz:
http://arxiv.org/abs/2409.00789
We consider the problem of learning a target function corresponding to a single hidden layer neural network, with a quadratic activation function after the first layer, and random weights. We consider the asymptotic limit where the input dimension an
Externí odkaz:
http://arxiv.org/abs/2408.03733
We consider the situation when a learner faces a set of unknown discrete distributions $(p_k)_{k\in \mathcal K}$ defined over a common alphabet $\mathcal X$, and can build for each distribution $p_k$ an individual high-probability confidence set than
Externí odkaz:
http://arxiv.org/abs/2407.15662
Monte-Carlo Tree Search (MCTS) is a widely-used strategy for online planning that combines Monte-Carlo sampling with forward tree search. Its success relies on the Upper Confidence bound for Trees (UCT) algorithm, an extension of the UCB method for m
Externí odkaz:
http://arxiv.org/abs/2406.02235
A major impediment to the advancement of sign language translation (SLT) is data scarcity. Much of the sign language data currently available on the web cannot be used for training supervised models due to the lack of aligned captions. Furthermore, s
Externí odkaz:
http://arxiv.org/abs/2402.09611
Autor:
Legrand, Alexandre, Maillard, Pascal
The $N$-particles branching Brownian motion ($N$-BBM) is a branching Markov process which describes the evolution of a population of particles undergoing reproduction and selection. It shares many properties with the $N$-particles branching random wa
Externí odkaz:
http://arxiv.org/abs/2402.04917
Publikováno v:
Phys. Rev. D 109, 023523, 2024
We present a signal-foreground separation algorithm for filtering observational data to extract spectral distortions of the cosmic microwave background (CMB). Our linear method, called the least response method (LRM), is based on the idea of simultan
Externí odkaz:
http://arxiv.org/abs/2401.13415
Autor:
Communication, Seamless, Barrault, Loïc, Chung, Yu-An, Meglioli, Mariano Coria, Dale, David, Dong, Ning, Duppenthaler, Mark, Duquenne, Paul-Ambroise, Ellis, Brian, Elsahar, Hady, Haaheim, Justin, Hoffman, John, Hwang, Min-Jae, Inaguma, Hirofumi, Klaiber, Christopher, Kulikov, Ilia, Li, Pengwei, Licht, Daniel, Maillard, Jean, Mavlyutov, Ruslan, Rakotoarison, Alice, Sadagopan, Kaushik Ram, Ramakrishnan, Abinesh, Tran, Tuan, Wenzek, Guillaume, Yang, Yilin, Ye, Ethan, Evtimov, Ivan, Fernandez, Pierre, Gao, Cynthia, Hansanti, Prangthip, Kalbassi, Elahe, Kallet, Amanda, Kozhevnikov, Artyom, Gonzalez, Gabriel Mejia, Roman, Robin San, Touret, Christophe, Wong, Corinne, Wood, Carleigh, Yu, Bokai, Andrews, Pierre, Balioglu, Can, Chen, Peng-Jen, Costa-jussà, Marta R., Elbayad, Maha, Gong, Hongyu, Guzmán, Francisco, Heffernan, Kevin, Jain, Somya, Kao, Justine, Lee, Ann, Ma, Xutai, Mourachko, Alex, Peloquin, Benjamin, Pino, Juan, Popuri, Sravya, Ropers, Christophe, Saleem, Safiyyah, Schwenk, Holger, Sun, Anna, Tomasello, Paden, Wang, Changhan, Wang, Jeff, Wang, Skyler, Williamson, Mary
Large-scale automatic speech translation systems today lack key features that help machine-mediated communication feel seamless when compared to human-to-human dialogue. In this work, we introduce a family of models that enable end-to-end expressive
Externí odkaz:
http://arxiv.org/abs/2312.05187