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stat.ML2023
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning
Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini +1
In this paper, we prove the first Bayesian regret bounds for Thompson Sampling in reinforcement learning in a multitude of settings. We simplify the learning problem using a discre…
stat.ML2016
Using Empirical Covariance Matrix in Enhancing Prediction Accuracy of Linear Models with Missing Information
Ahmadreza Moradipari, Sina Shahsavari, Ashkan Esmaeili +1
Inference and Estimation in Missing Information (MI) scenarios are important topics in Statistical Learning Theory and Machine Learning (ML). In ML literature, attempts have been m…