Adam Stooke

According to our database, Adam Stooke authored at least 14 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Massive End-to-end Speech Recognition Models with Time Reduction.

Weiran Wang, Rohit Prabhavalkar, Haozhe Shan, Zhong Meng, Dongseong Hwang, Qiujia Li, Khe Chai Sim, Bo Li, James Qin, Xingyu Cai, Adam Stooke, Chengjian Zheng, Yanzhang He, Tara N. Sainath, Pedro Moreno Mengibar

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

A Comparison of Parameter-Efficient ASR Domain Adaptation Methods for Universal Speech and Language Models.

Khe Chai Sim, Zhouyuan Huo, Tsendsuren Munkhdalai, Nikhil Siddhartha, Adam Stooke, Zhong Meng, Bo Li, Tara N. Sainath

Proceedings of the IEEE International Conference on Acoustics, 2024

Extreme Encoder Output Frame Rate Reduction: Improving Computational Latencies of Large End-to-End Models.

Rohit Prabhavalkar, Zhong Meng, Weiran Wang, Adam Stooke, Xingyu Cai, Yanzhang He, Arun Narayanan, Dongseong Hwang, Tara N. Sainath, Pedro J. Moreno

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Massive End-to-end Models for Short Search Queries.

Weiran Wang, Rohit Prabhavalkar, Dongseong Hwang, Qiujia Li, Khe Chai Sim, Bo Li, James Qin, Xingyu Cai, Adam Stooke, Zhong Meng, CJ Zheng, Yanzhang He, Tara N. Sainath, Pedro Moreno Mengibar

CoRR, 2023

2022

Internal Language Model Personalization of E2E Automatic Speech Recognition Using Random Encoder Features.

Adam Stooke, Khe Chai Sim, Mason Chua, Tsendsuren Munkhdalai, Trevor Strohman

Proceedings of the IEEE Spoken Language Technology Workshop, 2022

2021

Open-Ended Learning Leads to Generally Capable Agents.

Open Ended Learning Team, Adam Stooke, Anuj Mahajan, Catarina Barros, Charlie Deck, Jakob Bauer, Jakub Sygnowski, Maja Trebacz, Max Jaderberg, Michaël Mathieu, Nat McAleese, Nathalie Bradley-Schmieg, Nathaniel Wong, Nicolas Porcel, Roberta Raileanu, Steph Hughes-Fitt, Valentin Dalibard, Wojciech Marian Czarnecki

CoRR, 2021

Decoupling Representation Learning from Reinforcement Learning.

Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Perception-Prediction-Reaction Agents for Deep Reinforcement Learning.

Adam Stooke, Valentin Dalibard, Siddhant M. Jayakumar, Wojciech M. Czarnecki, Max Jaderberg

CoRR, 2020

Reinforcement Learning with Augmented Data.

Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Responsive Safety in Reinforcement Learning by PID Lagrangian Methods.

Adam Stooke, Joshua Achiam, Pieter Abbeel

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch.

Adam Stooke, Pieter Abbeel

CoRR, 2019

2018

Accelerated Methods for Deep Reinforcement Learning.

Adam Stooke, Pieter Abbeel

CoRR, 2018

2017

Synkhronos: a Multi-GPU Theano Extension for Data Parallelism.

Adam Stooke, Pieter Abbeel

CoRR, 2017

#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning.

Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017