Abram L. Friesen

According to our database, Abram L. Friesen authored at least 19 papers between 2010 and 2023.

Collaborative distances:

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

2023

Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning.

Patrick Emedom-Nnamdi, Abram L. Friesen, Bobak Shahriari, Nando de Freitas, Matthew W. Hoffman

CoRR, 2023

2022

Multi-step Planning for Automated Hyperparameter Optimization with OptFormer.

Lucio M. Dery, Abram L. Friesen, Nando de Freitas, Marc'Aurelio Ranzato, Yutian Chen

CoRR, 2022

Retrieval-Augmented Reinforcement Learning.

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

CoRR, 2022

Retrieval-Augmented Reinforcement Learning.

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

Proceedings of the International Conference on Machine Learning, 2022

Model-Value Inconsistency as a Signal for Epistemic Uncertainty.

Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal M. P. Behbahani, Tom Schaul, André Barreto, Simon Osindero

Proceedings of the International Conference on Machine Learning, 2022

Introducing Symmetries to Black Box Meta Reinforcement Learning.

Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

On the role of planning in model-based deep reinforcement learning.

Jessica B. Hamrick, Abram L. Friesen, Feryal M. P. Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Holger Buesing, Petar Velickovic, Theophane Weber

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Modular Meta-Learning with Shrinkage.

Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas

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

2018

Submodular Field Grammars: Representation, Inference, and Application to Image Parsing.

Abram L. Friesen, Pedro M. Domingos

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Learning as a Mixed Convex-Combinatorial Optimization Problem.

Abram L. Friesen, Pedro M. Domingos

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

The Sum-Product Theorem and its Applications.

Abram L. Friesen

PhD thesis, 2017

2016

Recursive Decomposition for Nonconvex Optimization.

Abram L. Friesen, Pedro M. Domingos

CoRR, 2016

The Sum-Product Theorem: A Foundation for Learning Tractable Models.

Abram L. Friesen, Pedro M. Domingos

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Recursive Decomposition for Nonconvex Optimization - IJCAI-15 Distinguished Paper.

Abram L. Friesen, Pedro M. Domingos

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2012

How Prior Probability Influences Decision Making: A Unifying Probabilistic Model.

Yanping Huang, Abram L. Friesen, Timothy D. Hanks, Michael N. Shadlen, Rajesh P. N. Rao

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

An ideal observer model for identifying the reference frame of objects.

Joseph L. Austerweil, Abram L. Friesen, Thomas L. Griffiths

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Gaze Following as Goal Inference: A Bayesian Model.

Abram L. Friesen, Rajesh P. N. Rao

Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

2010

Imitation learning with hierarchical actions.

Abram L. Friesen, Rajesh P. N. Rao

Proceedings of the 2010 IEEE 9th International Conference on Development and Learning, 2010

Estimating the progress of MapReduce pipelines.

Kristi Morton, Abram L. Friesen, Magdalena Balazinska, Dan Grossman

Proceedings of the 26th International Conference on Data Engineering, 2010