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Convergence Guarantees for Deep Epsilon Greedy Policy Learning

Convergence Guarantees for Deep Epsilon Greedy Policy Learning

Michael Rawson
R. Balan
ArXivPDFHTML

Papers citing "Convergence Guarantees for Deep Epsilon Greedy Policy Learning"

5 / 5 papers shown
Title
A Generative Framework for Predictive Modeling of Multiple Chronic Conditions Using Graph Variational Autoencoder and Bandit-Optimized Graph Neural Network
A Generative Framework for Predictive Modeling of Multiple Chronic Conditions Using Graph Variational Autoencoder and Bandit-Optimized Graph Neural Network
Julian Carvajal Rico
A. Alaeddini
Syed Hasib Akhter Faruqui
S. Fisher-Hoch
J. McCormick
63
0
0
13 Mar 2025
Urban Computing for Climate and Environmental Justice: Early Perspectives From Two Research Initiatives
Urban Computing for Climate and Environmental Justice: Early Perspectives From Two Research Initiatives
Carolina Veiga
Ashish Sharma
Daniel de Oliveira
Marcos Lage
Fabio Miranda
AI4CE
27
0
0
06 Oct 2024
Optimal Policy Learning with Observational Data in Multi-Action Scenarios: Estimation, Risk Preference, and Potential Failures
Optimal Policy Learning with Observational Data in Multi-Action Scenarios: Estimation, Risk Preference, and Potential Failures
Giovanni Cerulli
OffRL
24
0
0
29 Mar 2024
A Deep Reinforcement Learning Approach for Interactive Search with Sentence-level Feedback
A Deep Reinforcement Learning Approach for Interactive Search with Sentence-level Feedback
Jianghong Zhou
Joyce C. Ho
Chen Lin
Eugene Agichtein
23
0
0
03 Oct 2023
Optimal Transport for Super Resolution Applied to Astronomy Imaging
Optimal Transport for Super Resolution Applied to Astronomy Imaging
Michael Rawson
Jakob Hultgren
OT
6
0
0
10 Feb 2022