Abram L. Friesen

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 18

Top Topics

Reinforcement Learning

Convex Optimization

Top Venues

Publications

Patrick Emedom-Nnamdi, Abram L. Friesen, Bobak Shahriari, Nando de Freitas, Matthew W. Hoffman
Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning. CoRR (2023)
Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Peter C. Humphreys, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell
Retrieval-Augmented Reinforcement Learning. ICML (2022)
Lucio M. Dery, Abram L. Friesen, Nando de Freitas, Marc'Aurelio Ranzato, Yutian Chen
Multi-step Planning for Automated Hyperparameter Optimization with OptFormer. CoRR (2022)
Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen
Introducing Symmetries to Black Box Meta Reinforcement Learning. AAAI (2022)
Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal Behbahani, Tom Schaul, André Barreto, Simon Osindero
Model-Value Inconsistency as a Signal for Epistemic Uncertainty. ICML (2022)
Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell
Retrieval-Augmented Reinforcement Learning. CoRR (2022)
Jessica B. Hamrick, Abram L. Friesen, Feryal Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Holger Buesing, Petar Velickovic, Theophane Weber
On the role of planning in model-based deep reinforcement learning. ICLR (2021)
Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal Behbahani, Tom Schaul, André Barreto, Simon Osindero
Model-Value Inconsistency as a Signal for Epistemic Uncertainty. CoRR (2021)
Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen
Introducing Symmetries to Black Box Meta Reinforcement Learning. CoRR (2021)
Yutian Chen, Abram L. Friesen, Feryal Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas
Modular Meta-Learning with Shrinkage. NeurIPS (2020)
Jessica B. Hamrick, Abram L. Friesen, Feryal Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Buesing, Petar Velickovic, Théophane Weber
On the role of planning in model-based deep reinforcement learning. CoRR (2020)
Yutian Chen, Abram L. Friesen, Feryal Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas
Modular Meta-Learning with Shrinkage. CoRR (2019)
Abram L. Friesen, Pedro M. Domingos
Submodular Field Grammars: Representation, Inference, and Application to Image Parsing. NeurIPS (2018)
Abram L. Friesen, Pedro M. Domingos
Deep Learning as a Mixed Convex-Combinatorial Optimization Problem. ICLR (Poster) (2018)
Abram L. Friesen, Pedro M. Domingos
Deep Learning as a Mixed Convex-Combinatorial Optimization Problem. CoRR (2017)
Abram L. Friesen, Pedro M. Domingos
Recursive Decomposition for Nonconvex Optimization. CoRR (2016)
Abram L. Friesen, Pedro M. Domingos
The Sum-Product Theorem: A Foundation for Learning Tractable Models. CoRR (2016)
Abram L. Friesen, Pedro M. Domingos
The Sum-Product Theorem: A Foundation for Learning Tractable Models. ICML (2016)
Abram L. Friesen, Pedro M. Domingos
Recursive Decomposition for Nonconvex Optimization - IJCAI-15 Distinguished Paper. IJCAI (2015)
Yanping Huang, Abram L. Friesen, Timothy D. Hanks, Michael N. Shadlen, Rajesh P. N. Rao
How Prior Probability Influences Decision Making: A Unifying Probabilistic Model. NIPS (2012)
Abram L. Friesen, Rajesh P. N. Rao
Gaze Following as Goal Inference: A Bayesian Model. CogSci (2011)
Joseph L. Austerweil, Abram L. Friesen, Thomas L. Griffiths
An ideal observer model for identifying the reference frame of objects. NIPS (2011)
Abram L. Friesen, Rajesh P. N. Rao
Imitation learning with hierarchical actions. ICDL (2010)
Kristi Morton, Abram L. Friesen, Magdalena Balazinska, Dan Grossman
Estimating the progress of MapReduce pipelines. ICDE (2010)