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Every Model Learned by Gradient Descent Is Approximately a Kernel Machine


Nov 30, 2020
Pedro Domingos

* 12 pages, 2 figures 

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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

* In Proceedings of the International Conference on Learning Representations (ICLR) 2018 
* 14 pages (9 body, 5 pages of references and appendices) 

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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

* 58 pages, work in progress 

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


Nov 11, 2016
Abram L. Friesen, Pedro Domingos

* Proceedings of the 33rd International Conference on Machine Learning, pp. 1909-1918, 2016 
* 15 pages (10 body, 5 pages of appendices) 

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Recursive Decomposition for Nonconvex Optimization


Nov 08, 2016
Abram L. Friesen, Pedro Domingos

* Proceedings of the 24th International Joint Conference on Artificial Intelligence (2015), pp. 253-259 
* 11 pages, 7 figures, pdflatex 

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On the Latent Variable Interpretation in Sum-Product Networks


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

* Revised version, accepted for publication in IEEE Transactions on Machine Intelligence and Pattern Analysis (TPAMI). Shortened and revised Section 4: Thanks to our reviewers, pointing out that Theorem 2 holds for selective SPNs. Added paragraph in Section 2.1, relating sizes of original/augmented SPNs. Fixed typos, rephrased sentences, revised references 

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Learning Tractable Probabilistic Models for Fault Localization


Jul 07, 2015
Aniruddh Nath, Pedro Domingos

* Fifth International Workshop on Statistical Relational AI (StaR-AI 2015) 

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Exchangeable Variable Models


May 02, 2014
Mathias Niepert, Pedro Domingos

* ICML 2014 

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Structured Message Passing


Sep 26, 2013
Vibhav Gogate, Pedro Domingos

* Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013) 

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Markov Logic in Infinite Domains


Jun 20, 2012
Parag Singla, Pedro Domingos

* Appears in Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (UAI2007) 

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Learning Arithmetic Circuits


Jun 13, 2012
Daniel Lowd, Pedro Domingos

* Appears in Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI2008) 

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Formula-Based Probabilistic Inference


Mar 15, 2012
Vibhav Gogate, Pedro Domingos

* Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010) 

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Approximation by Quantization


Feb 14, 2012
Vibhav Gogate, Pedro Domingos


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Probabilistic Theorem Proving


Feb 14, 2012
Vibhav Gogate, Pedro Domingos


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Sum-Product Networks: A New Deep Architecture


Feb 14, 2012
Hoifung Poon, Pedro Domingos


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