Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Bhargava, Aniruddha"'
Last-mile carriers increasingly incorporate electric vehicles (EVs) into their delivery fleet to achieve sustainability goals. This goal presents many challenges across multiple planning spaces including but not limited to how to plan EV routes. In t
Externí odkaz:
http://arxiv.org/abs/2408.12006
Learning from human feedback has been central to recent advances in artificial intelligence and machine learning. Since the collection of human feedback is costly, a natural question to ask is if the new feedback always needs to collected. Or could w
Externí odkaz:
http://arxiv.org/abs/2406.10030
Autor:
Alizadeh, Shima, Bhargava, Aniruddha, Gopalswamy, Karthick, Jain, Lalit, Kveton, Branislav, Liu, Ge
Multi-objective optimization is a type of decision making problems where multiple conflicting objectives are optimized. We study offline optimization of multi-objective policies from data collected by an existing policy. We propose a pessimistic esti
Externí odkaz:
http://arxiv.org/abs/2310.18617
This paper explores a new form of the linear bandit problem in which the algorithm receives the usual stochastic rewards as well as stochastic feedback about which features are relevant to the rewards, the latter feedback being the novel aspect. The
Externí odkaz:
http://arxiv.org/abs/1903.03705
Generalized Linear Bandits (GLBs), a natural extension of the stochastic linear bandits, has been popular and successful in recent years. However, existing GLBs scale poorly with the number of rounds and the number of arms, limiting their utility in
Externí odkaz:
http://arxiv.org/abs/1706.00136
In this paper we model the problem of learning preferences of a population as an active learning problem. We propose an algorithm can adaptively choose pairs of items to show to users coming from a heterogeneous population, and use the obtained rewar
Externí odkaz:
http://arxiv.org/abs/1603.04118
Many real-world phenomena can be represented by a spatio-temporal signal: where, when, and how much. Social media is a tantalizing data source for those who wish to monitor such signals. Unlike most prior work, we assume that the target phenomenon is
Externí odkaz:
http://arxiv.org/abs/1204.2248
Akademický článek
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Publikováno v:
Machine Learning & Knowledge Discovery in Databases (9783642334856); 2012, p644-659, 16p