Greaves, Joshua

9 publications

NeurIPS 2025 Tapered Off-Policy REINFORCE - Stable and Efficient Reinforcement Learning for Large Language Models Nicolas Le Roux, Marc G Bellemare, Jonathan Lebensold, Arnaud Bergeron, Joshua Greaves, Alexandre Fréchette, Carolyne Pelletier, Eric Thibodeau-Laufer, Sándor Tóth, Sam Work

AISTATS 2023 A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare

NeurIPSW 2023 Learning Silicon Dopant Transitions in Graphene Using Scanning Transmission Electron Microscopy Max Schwarzer, Jesse Farebrother, Joshua Greaves, Kevin Roccapriore, Ekin Cubuk, Rishabh Agarwal, Aaron Courville, Marc Bellemare, Sergei Kalinin, Igor Mordatch, Pablo Castro

ICLR 2023 Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G Bellemare

NeurIPSW 2022 A Novel Stochastic Gradient Descent Algorithm for LearningPrincipal Subspaces Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G Bellemare

NeurIPSW 2022 Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G Bellemare

NeurIPSW 2022 Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G Bellemare

NeurIPSW 2022 Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G Bellemare

WACV 2021 Multi-Path Neural Networks for On-Device Multi-Domain Visual Classification Qifei Wang, Junjie Ke, Joshua Greaves, Grace Chu, Gabriel Bender, Luciano Sbaiz, Alec Go, Andrew Howard, Ming-Hsuan Yang, Jeff Gilbert, Peyman Milanfar, Feng Yang