Loss Functions: Policy Learning

Loss Functions: Policy Learning

Direct Preference Optimization (DPO) explained: Bradley-Terry model, log probabilities, mathПодробнее

Direct Preference Optimization (DPO) explained: Bradley-Terry model, log probabilities, math

Reinforcement Learning from Human Feedback explained with math derivations and the PyTorch code.Подробнее

Reinforcement Learning from Human Feedback explained with math derivations and the PyTorch code.

Learning Generalized Policies Without Supervision Using GNNs – Contributed talk – PRL @ ICAPS 2022Подробнее

Learning Generalized Policies Without Supervision Using GNNs – Contributed talk – PRL @ ICAPS 2022

Loss Functions for Causal InferenceПодробнее

Loss Functions for Causal Inference

DPO Debate: Is RL needed for RLHF?Подробнее

DPO Debate: Is RL needed for RLHF?

Coding chatGPT from Scratch | Lecture 2: PPO ImplementationПодробнее

Coding chatGPT from Scratch | Lecture 2: PPO Implementation

ACM Goa - Talk by Prof. Snehanshu Saha: on Learning Rates and Loss FunctionsПодробнее

ACM Goa - Talk by Prof. Snehanshu Saha: on Learning Rates and Loss Functions

Loss Functions: Treatment HeterogeneityПодробнее

Loss Functions: Treatment Heterogeneity

Sarah Bechtle on Lifelong Learning in the Real World | Toronto AIR SeminarПодробнее

Sarah Bechtle on Lifelong Learning in the Real World | Toronto AIR Seminar

Franziska Meier @ RSS20 Workshop on Action Representations for Learning in Continuous ControlПодробнее

Franziska Meier @ RSS20 Workshop on Action Representations for Learning in Continuous Control

Introduction to Reinforcement Learning (Lecture 05 - Value Function Approximation) (Part 2)Подробнее

Introduction to Reinforcement Learning (Lecture 05 - Value Function Approximation) (Part 2)

VeA/RTU 2021 Q1 - 17. Policy Gradient (Reinforcement Learning)Подробнее

VeA/RTU 2021 Q1 - 17. Policy Gradient (Reinforcement Learning)

Imitation Learning from MPC for Quadrupedal Multi-Gait Control (ICRA 2021 Presentation)Подробнее

Imitation Learning from MPC for Quadrupedal Multi-Gait Control (ICRA 2021 Presentation)

Gradients are Not All You Need (Machine Learning Research Paper Explained)Подробнее

Gradients are Not All You Need (Machine Learning Research Paper Explained)

13. Module 4- Insurance- Principles of Insurance- Functions of Insurance. 9995177575Подробнее

13. Module 4- Insurance- Principles of Insurance- Functions of Insurance. 9995177575

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study (Paper Explained)Подробнее

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study (Paper Explained)

ICRA 2020 Plenary Talk: Yann LeCun -- Self-Supervised Learning & World ModelsПодробнее

ICRA 2020 Plenary Talk: Yann LeCun -- Self-Supervised Learning & World Models

USENIX Security '21 - Adversarial Policy Training against Deep Reinforcement LearningПодробнее

USENIX Security '21 - Adversarial Policy Training against Deep Reinforcement Learning

Self-Driving Cars - Lecture 4.1 (Reinforcement Learning: Markov Decision Processes)Подробнее

Self-Driving Cars - Lecture 4.1 (Reinforcement Learning: Markov Decision Processes)