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Lecture 2 | Multi-arm Bandits | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes
Lecture 1 | Machine Learning Paradigms - An Overview | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes
Lecture 13 | Value Iteration and Monte Carlo Prediction | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes
Lecture 10 - Bellman Expectation Equations for MDP | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes
Lecture 11 | Bellman Optimality Eqs | Policy Iteration | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes
Lecture 12 | Convergence Proof of Policy Iteration | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes
Lecture 4 - Regret Analysis of UCB Bandit algorithm | Reinforcement Learning | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes
Lecture 5 - UCB Regret | KL Divergence | B–H inequality | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes
Lecture 6 - Lower Bound on Regret for Bandit Algorithms | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes
Lecture 7 - Thompson Sampling for Multi-arm Bandits | Reinforcement Learning Course | IIT KanpurEE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur Notes

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