Zobrazeno 1 - 10
of 242
pro vyhledávání: '"Meir, Ron"'
Autor:
Friedman, Lior, Meir, Ron
In continual learning, knowledge must be preserved and re-used between tasks, maintaining good transfer to future tasks and minimizing forgetting of previously learned ones. While several practical algorithms have been devised for this setting, there
Externí odkaz:
http://arxiv.org/abs/2406.09370
Given a time-series of noisy measured outputs of a dynamical system z[k], k=1...N, the Identifying Regulation with Adversarial Surrogates (IRAS) algorithm aims to find a non-trivial first integral of the system, namely, a scalar function g() such tha
Externí odkaz:
http://arxiv.org/abs/2405.02953
Artificial agents that learn to communicate in order to accomplish a given task acquire communication protocols that are typically opaque to a human. A large body of work has attempted to evaluate the emergent communication via various evaluation mea
Externí odkaz:
http://arxiv.org/abs/2403.14705
We consider a statistical version of curriculum learning (CL) in a parametric prediction setting. The learner is required to estimate a target parameter vector, and can adaptively collect samples from either the target model, or other source models t
Externí odkaz:
http://arxiv.org/abs/2402.13366
Whenever inspected by humans, reconstructed signals should not be distinguished from real ones. Typically, such a high perceptual quality comes at the price of high reconstruction error, and vice versa. We study this distortion-perception (DP) tradeo
Externí odkaz:
http://arxiv.org/abs/2402.02265
Autor:
Khodak, Mikhail, Osadchiy, Ilya, Harris, Keegan, Balcan, Maria-Florina, Levy, Kfir Y., Meir, Ron, Wu, Zhiwei Steven
We study online meta-learning with bandit feedback, with the goal of improving performance across multiple tasks if they are similar according to some natural similarity measure. As the first to target the adversarial online-within-online partial-inf
Externí odkaz:
http://arxiv.org/abs/2307.02295
Many practical settings call for the reconstruction of temporal signals from corrupted or missing data. Classic examples include decoding, tracking, signal enhancement and denoising. Since the reconstructed signals are ultimately viewed by humans, it
Externí odkaz:
http://arxiv.org/abs/2306.02400
The field of emergent communication aims to understand the characteristics of communication as it emerges from artificial agents solving tasks that require information exchange. Communication with discrete messages is considered a desired characteris
Externí odkaz:
http://arxiv.org/abs/2211.02412
We present a PAC-Bayes-style generalization bound which enables the replacement of the KL-divergence with a variety of Integral Probability Metrics (IPM). We provide instances of this bound with the IPM being the total variation metric and the Wasser
Externí odkaz:
http://arxiv.org/abs/2207.00614
We study meta-learning for adversarial multi-armed bandits. We consider the online-within-online setup, in which a player (learner) encounters a sequence of multi-armed bandit episodes. The player's performance is measured as regret against the best
Externí odkaz:
http://arxiv.org/abs/2205.15921