TalkRL: The Reinforcement Learning Podcast Robin Ranjit Singh Chauhan
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- Technology
TalkRL podcast is All Reinforcement Learning, All the Time.
In-depth interviews with brilliant people at the forefront of RL research and practice.
Guests from places like MILA, OpenAI, MIT, DeepMind, Berkeley, Amii, Oxford, Google Research, Brown, Waymo, Caltech, and Vector Institute.
Hosted by Robin Ranjit Singh Chauhan.
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Vincent Moens on TorchRL
Dr. Vincent Moens is an Applied Machine Learning Research Scientist at Meta, and an author of TorchRL and TensorDict in pytorch.
Featured References
TorchRL: A data-driven decision-making library for PyTorch Albert Bou, Matteo Bettini, Sebastian Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fabritiis, Vincent Moens
Additional References
TorchRL on github TensorDict Documentation -
Arash Ahmadian on Rethinking RLHF
Arash Ahmadian is a Researcher at Cohere and Cohere For AI focussed on Preference Training of large language models. He’s also a researcher at the Vector Institute of AI.
Featured Reference
Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs
Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker
Additional References
Self-Rewarding Language Models, Yuan et al 2024 Reinforcement Learning: An Introduction, Sutton and Barto 1992Learning from Delayed Rewards, Chris Watkins 1989Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning, Williams 1992 -
Glen Berseth on RL Conference
Glen Berseth is an assistant professor at the Université de Montréal, a core academic member of the Mila - Quebec AI Institute, a Canada CIFAR AI chair, member l'Institute Courtios, and co-director of the Robotics and Embodied AI Lab (REAL).
Featured Links
Reinforcement Learning Conference
Closing the Gap between TD Learning and Supervised Learning--A Generalisation Point of View Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach -
Ian Osband
Ian Osband is a Research scientist at OpenAI (ex DeepMind, Stanford) working on decision making under uncertainty.
We spoke about:
- Information theory and RL
- Exploration, epistemic uncertainty and joint predictions
- Epistemic Neural Networks and scaling to LLMs
Featured References
Reinforcement Learning, Bit by Bit Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen
From Predictions to Decisions: The Importance of Joint Predictive Distributions
Zheng Wen, Ian Osband, Chao Qin, Xiuyuan Lu, Morteza Ibrahimi, Vikranth Dwaracherla, Mohammad Asghari, Benjamin Van Roy
Epistemic Neural Networks
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
Approximate Thompson Sampling via Epistemic Neural Networks
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy
Additional References
Thesis defence, Ian Osband Homepage, Ian Osband Epistemic Neural Networks at Stanford RL Forum Behaviour Suite for Reinforcement Learning, Osband et al 2019 Efficient Exploration for LLMs, Dwaracherla et al 2024 -
Sharath Chandra Raparthy
Sharath Chandra Raparthy on In-Context Learning for Sequential Decision Tasks, GFlowNets, and more!
Sharath Chandra Raparthy is an AI Resident at FAIR at Meta, and did his Master's at Mila.
Featured Reference Generalization to New Sequential Decision Making Tasks with In-Context Learning Sharath Chandra Raparthy , Eric Hambro, Robert Kirk , Mikael Henaff, , Roberta Raileanu Additional References
Sharath Chandra Raparthy Homepage Human-Timescale Adaptation in an Open-Ended Task Space, Adaptive Agent Team 2023Data Distributional Properties Drive Emergent In-Context Learning in Transformers, Chan et al 2022 Decision Transformer: Reinforcement Learning via Sequence Modeling, Chen et al 2021 -
Pierluca D'Oro and Martin Klissarov
Pierluca D'Oro and Martin Klissarov on Motif and RLAIF, Noisy Neighborhoods and Return Landscapes, and more!
Pierluca D'Oro is PhD student at Mila and visiting researcher at Meta.
Martin Klissarov is a PhD student at Mila and McGill and research scientist intern at Meta.
Featured References
Motif: Intrinsic Motivation from Artificial Intelligence Feedback Martin Klissarov*, Pierluca D'Oro*, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control Nate Rahn*, Pierluca D'Oro*, Harley Wiltzer, Pierre-Luc Bacon, Marc G. Bellemare
To keep doing RL research, stop calling yourself an RL researcher Pierluca D'Oro