Abram (Abe) Friesen
Abram (Abe) Friesen
Research Scientist, DeepMind
Verified email at cs.washington.edu - Homepage
Title
Cited by
Cited by
Year
Estimating the progress of MapReduce pipelines
K Morton, AL Friesen, M Balazinska, D Grossman
Data Engineering (ICDE), 2010 IEEE 26th International Conference on, 681-684, 2010
1662010
Recursive decomposition for nonconvex optimization
AL Friesen, P Domingos
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
282015
How prior probability influences decision making: A unifying probabilistic model
Y Huang, AL Friesen, T Hanks, M Shadlen, RP Rao
Advances in neural information processing systems, 1268-1276, 2012
242012
The sum-product theorem: A foundation for learning tractable models
AL Friesen, P Domingos
International Conference on Machine Learning, 1909-1918, 2016
192016
Deep learning as a mixed convex-combinatorial optimization problem
AL Friesen, P Domingos
arXiv preprint arXiv:1710.11573, 2017
122017
Gaze following as goal inference: A Bayesian model
AL Friesen, RPN Rao
Proceedings of the Annual Meeting of the Cognitive Science Society 33 (33), 2011
122011
Imitation learning with hierarchical actions
AL Friesen, RPN Rao
2010 IEEE 9th International Conference on Development and Learning, 263-268, 2010
112010
A Bayesian developmental approach to robotic goal-based imitation learning
MJY Chung, AL Friesen, D Fox, AN Meltzoff, RPN Rao
PloS one 10 (11), 2015
92015
An ideal observer model for identifying the reference frame of objects
JL Austerweil, AL Friesen, TL Griffiths
Advances in neural information processing systems, 514-522, 2011
32011
Unifying Sum-Product Networks and Submodular Fields
AL Friesen, P Domingos
Proceedings of the Workshop on Principled Approaches to Deep Learning at ICML, 2017
22017
Submodular field grammars: representation, inference, and application to image parsing
AL Friesen, PM Domingos
Advances in Neural Information Processing Systems, 4307-4317, 2018
12018
The Sum-Product Theorem and its Applications
A Friesen
2017
Submodular Sum-product Networks for Scene Understanding
AL Friesen, P Domingos
2016
Unifying Sum-Product Networks and Submodular Fields (Supplementary Material)
AL Friesen, P Domingos
The Sum-Product Theorem: A Foundation for Learning Tractable Models (Supplementary Material)
AL Friesen, P Domingos
Exploiting Structure for Tractable Nonconvex Optimization
AL Friesen, W EDU, P Domingos
Nonconvex Optimization Is Combinatorial Optimization
AL Friesen, P Domingos
How Prior Probability Influences Decision Making: A Unifying Probabilistic Model
AL Friesen, Y Huang, MN Shadlen, TD Hanks, RPN Rao
Decision Making 2, 2.1, 0
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Articles 1–18