Results 31 to 40 of about 497,803 (209)
On-Line Adaptation of Exploration in the One-Armed Bandit with Covariates Problem
, 2010 Many sequential decision making problems require an agent to balance exploration and exploitation to maximise long-term reward. Existing policies that address this tradeoff typically have parameters that are set a priori to control the amount of ...
Sykulski, Adam M. +2 more
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Review of Social Media Sentiment and Contextual Bandit Models in Stock Market Investment [PDF]
ITM Web of ConferencesIn recent years, social media has become an important channel for investors to obtain market information, and investors are increasingly concerned about how emotional signals obtained from social media affect the stock market. With the profound impact of
Miao Ruicheng
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Semiparametric Contextual Bandits
CoRR, 2018 This paper studies semiparametric contextual bandits, a generalization of the linear stochastic bandit problem where the reward for an action is modeled as a linear function of known action features confounded by an non-linear action-independent term. We design new algorithms that achieve $\tilde{O}(d\sqrt{T})$ regret over $T$ rounds, when the linear ...
Akshay Krishnamurthy +2 more
openaire +4 more sources
Signal detection models as contextual bandits
Royal Society Open Science, 2023 Signal detection theory (SDT) has been widely applied to identify the optimal discriminative decisions of receivers under uncertainty. However, the approach assumes that decision-makers immediately adopt the appropriate acceptance threshold, even though ...
Thomas N. Sherratt, Erica O'Neill
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AdaptEx: A Self-Service Contextual Bandit Platform [PDF]
, 2023 This paper presents AdaptEx, a self-service contextual bandit platform widely used at Expedia Group, that leverages multi-armed bandit algorithms to personalize user experiences at scale. AdaptEx considers the unique context of each visitor to select the
Black, William +3 more
core +1 more source
Contextual Bandit with Missing Rewards
CoRR, 2020 We consider a novel variant of the contextual bandit problem (i.e., the multi-armed bandit with side-information, or context, available to a decision-maker) where the reward associated with each context-based decision may not always be observed("missing rewards").
Djallel Bouneffouf 0001 +2 more
openaire +3 more sources
Contextual Bandit Learning With Reward Oracles and Sampling Guidance in Multi-Agent Environments
IEEE Access, 2021 Learning action policy for autonomous agents in a decentralized multi-agent environment has remained an interesting but difficult research problem. We propose to model this problem in a contextual bandit setting with delayed reward signals, in particular
Mike Li, Quang Dang Nguyen
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Bandit Learning-Based Distributed Computation in Fog Computing Networks: A Survey
IEEE Access, 2023 Fog computing is a decentralized computing infrastructure that extends the capabilities of cloud computing closer to the edge of the network. In a fog computing network (FCN), computing resources, such as processing power, storage, and networking, are ...
Hoa Tran-Dang +2 more
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Mathematical Models and Algorithms for Contextual Multi-armed Bandit Problems [PDF]
, 2023 Η παρούσα διπλωματική εργασία αναφέρεται σε μια ειδική κατηγορία των προβλημάτων bandit, τα contextual bandits, καθώς και σε αλγορίθμους για προβλήματα εκμάθησης. Τα contextual bandits ανήκουν στον τομέα της ενισχυτικής μάθησης και σε ένα τέτοιο πρόβλημα,
Zacharis Dimitrios +1 more
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A Gaussian process approach for contextual bandit-based battery replacement [PDF]
ITM Web of ConferencesThe sharing economy has recently become a distinctive business model in China, offering advantages such as low prices and ease of use. Shared electric vehicles have also become an essential part of urban transportation.
Zhou Tianshi
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