policy gradient methods

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1. 1▶[UCLA RL-LLM] Chapter 2.4: In-context learning and instruction fine-tuningReinforcement Learning of Large Language ModelsNotes
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2. 2▶[UCLA RL-LLM] Chapter 2.3: Transformers II (modern transformers updates and sampling methods)Reinforcement Learning of Large Language ModelsNotes
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3. 3▶[UCLA RL-LLM] Chapter 2.2: Transformers I (BERT, GPT-1)Reinforcement Learning of Large Language ModelsNotes
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4. 4▶[UCLA RL-LLM] Chapter 2.1: NLP foundations, language modeling, RNNsReinforcement Learning of Large Language ModelsNotes
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5. 5▶[UCLA RL-LLM] Chapter 3.2: Reinforcement learning with verifiable rewards (RLVR)Reinforcement Learning of Large Language ModelsNotes
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6. 6▶[UCLA RL-LLM] Chapter 3.1: Reinforcement learning from human feedback (PPO, DPO)Reinforcement Learning of Large Language ModelsNotes
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7. 7▶[UCLA RL-LLM] Chapter 1.5: AlphaGo, test-time compute, and expert iterationReinforcement Learning of Large Language ModelsNotes
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8. 8▶[UCLA RL-LLM] Chapter 1.4: Deep policy gradient methods (PPO, GRPO)Reinforcement Learning of Large Language ModelsNotes
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9. 9▶[UCLA RL-LLM] Chapter 1.3: Deep policy gradient methods (A3C)Reinforcement Learning of Large Language ModelsNotes
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10. 10▶[UCLA RL-LLM] Chapter 1.2: Deep policy evaluationReinforcement Learning of Large Language ModelsNotes
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11. 11▶[UCLA RL-LLM] Chapter 1.1: MDP foundations, imitation learning, and value iterationReinforcement Learning of Large Language ModelsNotes
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12. 12▶[UCLA RL-LLM] Chapter 0: Course outline and prologueReinforcement Learning of Large Language ModelsNotes
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13. 13▶Outlook and Research Insights (Safe, Edge and Meta Reinforcement Learning - Lecture 14, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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14. 14▶Further Contemporary RL Algorithms (TRPO, PPO - Lecture 13, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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15. 15▶Deterministic Policy Gradient Methods (Lecture 12, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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16. 16▶Stochastic Policy Gradient Methods (Lecture 11, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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17. 17▶Value-Based Control with Function Approximation (Lecture 10, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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18. 18▶On-Policy Prediction with Function Approximation (Lecture 09, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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19. 19▶Function Approximation with Supervised Learning (Lecture 08, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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20. 20▶Planning and Learning with Tabular Methods (Lecture 07, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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21. 21▶Multi-Step Bootstrapping (Lecture 06, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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22. 22▶Temporal Difference Learning (Lecture 05, Summer 2023)Reinforcement Learning Course: Lectures (Summer 2023)Notes
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23. 23▶Lecture 01 IntroductionCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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24. 24▶Lecture 02 Markov Decision ProcessesCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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25. 25▶Lecture 03 Solving known MDPsCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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26. 26▶Lecture 04 Solving Known MDPsCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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27. 27▶Lecture 05 Monte Carlo MethodsCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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28. 28▶Lecture 06 Temporal Difference MethodCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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29. 29▶Lecture 07 Neural Networks Architectures for RLCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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30. 30▶Lecture 08 Function Approximation for PredictionCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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31. 31▶Lecture 09 Value FunctionCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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32. 32▶Lecture 10 Policy Gradient MethodsCMU: 2018 Fall: 10-703 Deep Reinforcement Learning and ControlNotes
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