Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Avner, Orly"'
Time series forecasting is critical in numerous real-world applications, requiring accurate predictions of future values based on observed patterns. While traditional forecasting techniques work well in in-domain scenarios with ample data, they strug
Externí odkaz:
http://arxiv.org/abs/2411.15743
Std $Q$-target is a conservative, actor-critic, ensemble, $Q$-learning-based algorithm, which is based on a single key $Q$-formula: $Q$-networks standard deviation, which is an "uncertainty penalty", and, serves as a minimalistic solution to the prob
Externí odkaz:
http://arxiv.org/abs/2402.05950
We introduce a method for inferring an explicit PDE from a data sample generated by previously unseen dynamics, based on a learned context. The training phase integrates knowledge of the form of the equation with a differential scheme, while the infe
Externí odkaz:
http://arxiv.org/abs/2303.15827
Autor:
Avner, Orly, Mannor, Shie
Communication networks shared by many users are a widespread challenge nowadays. In this paper we address several aspects of this challenge simultaneously: learning unknown stochastic network characteristics, sharing resources with other users while
Externí odkaz:
http://arxiv.org/abs/1808.04875
Autor:
Avner, Orly, Mannor, Shie
Inspired by cognitive radio networks, we consider a setting where multiple users share several channels modeled as a multi-user multi-armed bandit (MAB) problem. The characteristics of each channel are unknown and are different for each user. Each us
Externí odkaz:
http://arxiv.org/abs/1504.08167
Autor:
Avner, Orly, Mannor, Shie
We consider the problem of multiple users targeting the arms of a single multi-armed stochastic bandit. The motivation for this problem comes from cognitive radio networks, where selfish users need to coexist without any side communication between th
Externí odkaz:
http://arxiv.org/abs/1404.5421
We consider a multi-armed bandit problem where the decision maker can explore and exploit different arms at every round. The exploited arm adds to the decision maker's cumulative reward (without necessarily observing the reward) while the explored ar
Externí odkaz:
http://arxiv.org/abs/1205.2874
We propose an explainable method for solving Partial Differential Equations by using a contextual scheme called PDExplain. During the training phase, our method is fed with data collected from an operator-defined family of PDEs accompanied by the gen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::685c244482a2af779e2008d5efffcafd
http://arxiv.org/abs/2303.15827
http://arxiv.org/abs/2303.15827
Akademický článek
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Autor:
Avner, Orly, Mannor, Shie
Publikováno v:
2012 IEEE 27th Convention of Electrical & Electronics Engineers in Israel; 1/ 1/2012, p1-5, 5p
