Hausknecht, Matthew

11 publications

AutoML 2025 Syftr: Pareto-Optimal Generative AI Alexander Conway, Debadeepta Dey, Stefan Hackmann, Matthew Hausknecht, Michael Douglas Schmidt, Mark Lewis Steadman, Nick Volynets

NeurIPS 2022 MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew Hausknecht

ICLRW 2022 Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin

NeurIPS 2022 Uni[MASK]: Unified Inference in Sequential Decision Problems Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin

ICLR 2021 ALFWorld: Aligning Text and Embodied Environments for Interactive Learning Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Cote, Yonatan Bisk, Adam Trischler, Matthew Hausknecht

ICLR 2020 Graph Constrained Reinforcement Learning for Natural Language Action Spaces Prithviraj Ammanabrolu, Matthew Hausknecht

ICML 2020 Learning Calibratable Policies Using Programmatic Style-Consistency Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht

ICML 2020 Working Memory Graphs Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht

ICLR 2018 Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis Rudy Bunel, Matthew Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli

NeurIPS 2017 Neural Program Meta-Induction Jacob Devlin, Rudy R Bunel, Rishabh Singh, Matthew Hausknecht, Pushmeet Kohli

CVPR 2015 Beyond Short Snippets: Deep Networks for Video Classification Joe Yue-Hei Ng, Matthew Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici