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Efficient contextual partial monitoring with general function approximation
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arXiv Machine Learning
1d ago
Efficient contextual partial monitoring with general function approximation
arXiv:2610.19804v1 Announce Type: new Abstract: We study finite stochastic partial monitoring (PM) games with side information, a paradigm of sequential learning with partial feedback. On each round...
arXiv Machine Learning
Jul 31
On-Policy and Off-Policy Learning for Large Action Spaces
arXiv:2607. 28408v1 Announce Type: new Abstract: This thesis studies policy learning in interactive systems where an agent observes a context, selects an action from a very large set, and receives partial feedback.
arXiv Machine Learning
Jun 29
Taming the Monster Every Context: Complexity Measure and Unified Framework for Offline-Oracle Efficient Contextual Bandits
arXiv:2602. 09456v2 Announce Type: replace Abstract: We propose an algorithmic framework, Offline Estimation to Decisions (OE2D), that efficiently reduces contextual bandit learning with general reward function approximation to offline regression.
arXiv Machine Learning
Jul 14
Randomized Confidence Bounds for Stochastic Partial Monitoring
arXiv:2402. 05002v3 Announce Type: replace Abstract: The partial monitoring (PM) framework provides a theoretical formulation of sequential learning problems with incomplete feedback.
arXiv Machine Learning
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Learning to Route and Schedule LLMs from User Retrials via Contextual Queueing Bandits
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arXiv Machine Learning
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Regret, equilibrium, and learning in games: A guided tour
arXiv:2608. 09389v1 Announce Type: cross Abstract: This note aims to serve as an entry point to the literature on learning in games, a topic with significant theoretical appeal and a wide range of applications -- from machine learning and data science to economics and beyond.