Adam Stooke

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 19

Top Topics

Speech Recognition

Reinforcement Learning

Data Parallelism

Top Venues

Publications

Rohit Prabhavalkar, Zhong Meng, Weiran Wang, Adam Stooke, Xingyu Cai, Yanzhang He, Arun Narayanan, Dongseong Hwang, Tara N. Sainath, Pedro J. Moreno
Extreme Encoder Output Frame Rate Reduction: Improving Computational Latencies of Large End-to-End Models. CoRR (2024)
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
Massive End-to-end Speech Recognition Models with Time Reduction. NAACL-HLT (2024)
Rohit Prabhavalkar, Zhong Meng, Weiran Wang, Adam Stooke, Xingyu Cai, Yanzhang He, Arun Narayanan, Dongseong Hwang, Tara N. Sainath, Pedro J. Moreno
Extreme Encoder Output Frame Rate Reduction: Improving Computational Latencies of Large End-to-End Models. ICASSP (2024)
Khe Chai Sim, Zhouyuan Huo, Tsendsuren Munkhdalai, Nikhil Siddhartha, Adam Stooke, Zhong Meng, Bo Li, Tara N. Sainath
A Comparison of Parameter-Efficient ASR Domain Adaptation Methods for Universal Speech and Language Models. ICASSP (2024)
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
Massive End-to-end Models for Short Search Queries. CoRR (2023)
Adam Stooke, Khe Chai Sim, Mason Chua, Tsendsuren Munkhdalai, Trevor Strohman
Internal Language Model Personalization of E2E Automatic Speech Recognition Using Random Encoder Features. SLT (2022)
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Decoupling Representation Learning from Reinforcement Learning. ICML (2021)
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
Open-Ended Learning Leads to Generally Capable Agents. CoRR (2021)
Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas
Reinforcement Learning with Augmented Data. CoRR (2020)
Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas
Reinforcement Learning with Augmented Data. NeurIPS (2020)
Adam Stooke, Valentin Dalibard, Siddhant M. Jayakumar, Wojciech M. Czarnecki, Max Jaderberg
Perception-Prediction-Reaction Agents for Deep Reinforcement Learning. CoRR (2020)
Adam Stooke, Joshua Achiam, Pieter Abbeel
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods. ICML (2020)
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Decoupling Representation Learning from Reinforcement Learning. CoRR (2020)
Adam Stooke, Joshua Achiam, Pieter Abbeel
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods. CoRR (2020)
Adam Stooke, Pieter Abbeel
rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch. CoRR (2019)
Adam Stooke, Pieter Abbeel
Accelerated Methods for Deep Reinforcement Learning. CoRR (2018)
Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning. NIPS (2017)
Adam Stooke, Pieter Abbeel
Synkhronos: a Multi-GPU Theano Extension for Data Parallelism. CoRR (2017)
Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning. CoRR (2016)