Zobrazeno 1 - 10
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pro vyhledávání: '"Data coverage"'
Autor:
Gibson, Jason B., Janicki, Tesia D., Hire, Ajinkya C., Bishop, Chris, Lane, J. Matthew D., Hennig, Richard G.
Machine-learned interatomic potentials (MLIPs) are becoming an essential tool in materials modeling. However, optimizing the generation of training data used to parameterize the MLIPs remains a significant challenge. This is because MLIPs can fail wh
Externí odkaz:
http://arxiv.org/abs/2409.07610
We initiate the study of Multi-Agent Reinforcement Learning from Human Feedback (MARLHF), exploring both theoretical foundations and empirical validations. We define the task as identifying Nash equilibrium from a preference-only offline dataset in g
Externí odkaz:
http://arxiv.org/abs/2409.00717
Autor:
La Sorte, Frank A.1,2 (AUTHOR) fl235@yale.edu, Cohen, Jeremy M.1,2 (AUTHOR), Jetz, Walter1,2 (AUTHOR)
Publikováno v:
Diversity & Distributions. Aug2024, Vol. 30 Issue 8, p1-13. 13p.
The goal of an offline reinforcement learning (RL) algorithm is to learn optimal polices using historical (offline) data, without access to the environment for online exploration. One of the main challenges in offline RL is the distribution shift whi
Externí odkaz:
http://arxiv.org/abs/2310.18434
Existing machine learning models have proven to fail when it comes to their performance for minority groups, mainly due to biases in data. In particular, datasets, especially social data, are often not representative of minorities. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2306.13868
Autor:
Weigell, Philipp
Volunteered Geographic Information projects like OpenStreetMap which allow accessing and using the raw data, are a treasure trove for investigations - e.g. cultural topics, urban planning, or accessibility of services. Among the concerns are the reli
Externí odkaz:
http://arxiv.org/abs/2306.04752
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This paper investigates when one can efficiently recover an approximate Nash Equilibrium (NE) in offline congestion games. The existing dataset coverage assumption in offline general-sum games inevitably incurs a dependency on the number of actions,
Externí odkaz:
http://arxiv.org/abs/2210.13396
The connected vehicle data (CVD) is one of the most promising emerging mobility data that greatly increases the ability to effectively monitor transportation system performance. A commercial vehicle trajectory dataset was evaluated for market penetra
Externí odkaz:
http://arxiv.org/abs/2208.04703
Akademický článek
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