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Thinking Fast and Slow in AI: the Role of Metacognition


Oct 05, 2021
Marianna Bergamaschi Ganapini, Murray Campbell, Francesco Fabiano, Lior Horesh, Jon Lenchner, Andrea Loreggia, Nicholas Mattei, Francesca Rossi, Biplav Srivastava, Kristen Brent Venable


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Integration of Data and Theory for Accelerated Derivable Symbolic Discovery


Sep 03, 2021
Cristina Cornelio, Sanjeeb Dash, Vernon Austel, Tyler Josephson, Joao Goncalves, Kenneth Clarkson, Nimrod Megiddo, Bachir El Khadir, Lior Horesh


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Quantum Topological Data Analysis with Linear Depth and Exponential Speedup


Aug 05, 2021
Shashanka Ubaru, Ismail Yunus Akhalwaya, Mark S. Squillante, Kenneth L. Clarkson, Lior Horesh

* 27 pages 

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E-PDDL: A Standardized Way of Defining Epistemic Planning Problems


Jul 19, 2021
Francesco Fabiano, Biplav Srivastava, Jonathan Lenchner, Lior Horesh, Francesca Rossi, Marianna Bergamaschi Ganapini

* 9 pages, Knowledge Engineering for Planning and Scheduling - ICAPS 2021 

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Denoising quantum states with Quantum Autoencoders -- Theory and Applications


Dec 29, 2020
Tom Achache, Lior Horesh, John Smolin

* 13 pages 

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Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra


Nov 12, 2020
Nadiia Chepurko, Kenneth L. Clarkson, Lior Horesh, David P. Woodruff

* Bibliographic edits 

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Projection techniques to update the truncated SVD of evolving matrices


Oct 13, 2020
Vassilis Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth L. Clarkson

* 13 pages 

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Thinking Fast and Slow in AI


Oct 12, 2020
Grady Booch, Francesco Fabiano, Lior Horesh, Kiran Kate, Jon Lenchner, Nick Linck, Andrea Loreggia, Keerthiram Murugesan, Nicholas Mattei, Francesca Rossi, Biplav Srivastava


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Symbolic Regression using Mixed-Integer Nonlinear Optimization


Jun 11, 2020
Vernon Austel, Cristina Cornelio, Sanjeeb Dash, Joao Goncalves, Lior Horesh, Tyler Josephson, Nimrod Megiddo


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Tensor Graph Convolutional Networks for Prediction on Dynamic Graphs


Oct 16, 2019
Osman Asif Malik, Shashanka Ubaru, Lior Horesh, Misha E. Kilmer, Haim Avron

* A shorter version of this paper was accepted as an extended abstract at the NeurIPS 2019 Workshop on Graph Representation Learning 

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Recurrent Neural Networks in the Eye of Differential Equations


Apr 29, 2019
Murphy Yuezhen Niu, Lior Horesh, Isaac Chuang

* 25pages, 3 figures 

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Stable Tensor Neural Networks for Rapid Deep Learning


Nov 15, 2018
Elizabeth Newman, Lior Horesh, Haim Avron, Misha Kilmer

* 20 pages, 6 figures, submitted to SIMODS 

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Globally Optimal Symbolic Regression


Nov 15, 2017
Vernon Austel, Sanjeeb Dash, Oktay Gunluk, Lior Horesh, Leo Liberti, Giacomo Nannicini, Baruch Schieber

* Presented at NIPS 2017 Symposium on Interpretable Machine Learning 

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Should You Derive, Or Let the Data Drive? An Optimization Framework for Hybrid First-Principles Data-Driven Modeling


Nov 12, 2017
Remi R. Lam, Lior Horesh, Haim Avron, Karen E. Willcox


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Image classification using local tensor singular value decompositions


Jun 29, 2017
Elizabeth Newman, Misha Kilmer, Lior Horesh

* Submitted to IEEE CAMSAP 2017 Conference, 5 pages, 9 figures and tables 

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Experimental Design for Non-Parametric Correction of Misspecified Dynamical Models


Jun 04, 2017
Gal Shulkind, Lior Horesh, Haim Avron

* A couple of (??) were corrected 

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Accelerating Hessian-free optimization for deep neural networks by implicit preconditioning and sampling


Dec 10, 2013
Tara N. Sainath, Lior Horesh, Brian Kingsbury, Aleksandr Y. Aravkin, Bhuvana Ramabhadran

* this paper is not supposed to be posted publically before the conference in December due to company policy. another co-author was not informed of this and posted without the permission of the first author. pls remove 

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