Jun 25, 2021 · We propose an adaptation of Knowledge Infused Policy Gradients to the Contextual Bandit setting and a novel Knowledge Infused Policy Gradients Upper Confidence ...
Relational boosted bandits, 2020. 9. Peter Auer, Nicolo Cesa-Bianchi, Yoav Freund, and Robert E Schapire. The non- stochastic multiarmed bandit problem.
Sep 10, 2021 · Abstract ; Transferable Contextual Bandits with Prior Observations · © 2021 ; Con-CNAME: A Contextual Multi-armed Bandit Algorithm for Personalized ...
Contextual Bandits find important use cases in various real-life scenarios such as online advertising, recommendation systems, healthcare, etc.
Sep 1, 2024 · We propose an adaptation of Knowledge Infused Policy Gradients to the Contextual Bandit setting and a novel Knowledge Infused Policy Gradients ...
Knowledge Infused Policy Gradients with Upper Confidence Bound for Relational Bandits ... Knowledge infused policy gradients for adaptive pandemic control.
Knowledge Infused Policy. Gradients Upper Confidence. Bound for Contextual Bandits. Adaptive Learning Agents Workshop @ AAMAS 2021. Page 2. Team. 2. Kaushik Roy.
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Knowledge infused policy gradients with upper confidence bound for relational bandits. K Roy, Q Zhang, M Gaur, A Sheth. Machine Learning and Knowledge Discovery ...
... Knowledge Infused Policy Gradients with Upper Confidence Bound for Relational Bandits”, ECML PKDD; Shrey Gupta, Anmol Agarwal, Manas Gaur, Kaushik Roy ...
"Knowledge infused policy gradients with upper confidence bound for relational bandits." In Joint European Conference on Machine Learning and Knowledge ...