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Pedro Domingos

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Every Model Learned by Gradient Descent Is Approximately a Kernel Machine

Nov 30, 2020
Pedro Domingos

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Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity

Sep 28, 2020
William Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Caelen Wang, Pedro Domingos, Siddhartha Srinivasa

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Self-Supervised Object-Level Deep Reinforcement Learning

Mar 03, 2020
William Agnew, Pedro Domingos

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Deep Learning as a Mixed Convex-Combinatorial Optimization Problem

Apr 16, 2018
Abram L. Friesen, Pedro Domingos

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Neural-Symbolic Learning and Reasoning: A Survey and Interpretation

Nov 10, 2017
Tarek R. Besold, Artur d'Avila Garcez, Sebastian Bader, Howard Bowman, Pedro Domingos, Pascal Hitzler, Kai-Uwe Kuehnberger, Luis C. Lamb, Daniel Lowd, Priscila Machado Vieira Lima, Leo de Penning, Gadi Pinkas, Hoifung Poon, Gerson Zaverucha

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

Nov 11, 2016
Abram L. Friesen, Pedro Domingos

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Recursive Decomposition for Nonconvex Optimization

Nov 08, 2016
Abram L. Friesen, Pedro Domingos

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On the Latent Variable Interpretation in Sum-Product Networks

Oct 28, 2016
Robert Peharz, Robert Gens, Franz Pernkopf, Pedro Domingos

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Learning Tractable Probabilistic Models for Fault Localization

Jul 07, 2015
Aniruddh Nath, Pedro Domingos

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Exchangeable Variable Models

May 02, 2014
Mathias Niepert, Pedro Domingos

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