Lior Horesh

Orcid: 0000-0001-6350-0238

According to our database1, Lior Horesh authored at least 73 papers between 2005 and 2024.

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Bibliography

2024
A Rational Filtering Algorithm for Sequences of Shifted Symmetric Linear Systems with Applications to Frequency Response Analysis.
SIAM J. Sci. Comput., 2024

Stable tensor neural networks for efficient deep learning.
Frontiers Big Data, 2024

On The Variance of Schatten <i>p</i>-Norm Estimation with Gaussian Sketching Matrices.
CoRR, 2024

Regenerative Ulam-von Neumann Algorithm: An Innovative Markov chain Monte Carlo Method for Matrix Inversion.
CoRR, 2024

Randomized linear solvers for computational architectures with straggling workers.
CoRR, 2024

Multivariate trace estimation using quantum state space linear algebra.
CoRR, 2024

Multi-Function Multi-Way Analog Technology for Sustainable Machine Intelligence Computation.
CoRR, 2024

Counting Triangles of Graphs via Matrix Partitioning.
Proceedings of the 34th IEEE International Workshop on Machine Learning for Signal Processing, 2024

Topological data analysis on noisy quantum computers.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS).
Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

Asynchronous Randomized Trace Estimation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Enhanced algebraic substructuring for symmetric generalized eigenvalue problems.
Numer. Linear Algebra Appl., March, 2023

Stable iterative refinement algorithms for solving linear systems.
CoRR, 2023

AI Hilbert: From Data and Background Knowledge to Automated Scientific Discovery.
CoRR, 2023

Understanding the Capabilities of Large Language Models for Automated Planning.
CoRR, 2023

Fast and Slow Planning.
CoRR, 2023

Plansformer Tool: Demonstrating Generation of Symbolic Plans Using Transformers.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Solving Sparse Linear Systems via Flexible GMRES with In-Memory Analog Preconditioning.
Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

Value-based Fast and Slow AI Nudging.
Proceedings of the Workshop on Ethics and Trust in Human-AI Collaboration: Socio-Technical Approaches (ETHAICS 2023) co-located with 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023) Macao, 2023

2022
On Quantum Algorithms for Random Walks in the Nonnegative Quarter Plane.
SIGMETRICS Perform. Evaluation Rev., August, 2022

Plansformer: Generating Symbolic Plans using Transformers.
CoRR, 2022

Bayesian Experimental Design for Symbolic Discovery.
CoRR, 2022

From String Detection to Orthogonal Vector Problem.
CoRR, 2022

Creating quantum-resistant classical-classical OWFs from quantum-classical OWFs.
CoRR, 2022

Towards Quantum Advantage on Noisy Quantum Computers.
CoRR, 2022

PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty.
CoRR, 2022

Efficient Quantum Computation of the Fermionic Boundary Operator.
CoRR, 2022

Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments.
CoRR, 2022

Distributed adversarial training to robustify deep neural networks at scale.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Overcoming Catastrophic Forgetting via Direction-Constrained Optimization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Combining Fast and Slow Thinking for Human-like and Efficient Decisions in Constrained Environments.
Proceedings of the 16th International Workshop on Neural-Symbolic Learning and Reasoning as part of the 2nd International Joint Conference on Learning & Reasoning (IJCLR 2022), 2022

Thinking Fast and Slow in AI: The Role of Metacognition.
Proceedings of the Machine Learning, Optimization, and Data Science, 2022

Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra.
Proceedings of the International Conference on Machine Learning, 2022

Decentralized Bilevel Optimization for Personalized Client Learning.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Fast Randomized Non-Hermitian Eigensolvers Based on Rational Filtering and Matrix Partitioning.
SIAM J. Sci. Comput., 2021

Dynamic graph and polynomial chaos based models for contact tracing data analysis and optimal testing prescription.
J. Biomed. Informatics, 2021

Integration of Data and Theory for Accelerated Derivable Symbolic Discovery.
CoRR, 2021

Quantum Topological Data Analysis with Linear Depth and Exponential Speedup.
CoRR, 2021

E-PDDL: A Standardized Way of Defining Epistemic Planning Problems.
CoRR, 2021

Solving sparse linear systems with approximate inverse preconditioners on analog devices.
CoRR, 2021

Fast randomized non-Hermitian eigensolver based on rational filtering and matrix partitioning.
CoRR, 2021

Dynamic Graph Convolutional Networks Using the Tensor M-Product.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Projection techniques to update the truncated SVD of evolving matrices with applications.
Proceedings of the 38th International Conference on Machine Learning, 2021

Training Logical Neural Networks by Primal-Dual Methods for Neuro-Symbolic Reasoning.
Proceedings of the IEEE International Conference on Acoustics, 2021

Sparse Graph Based Sketching for Fast Numerical Linear Algebra.
Proceedings of the IEEE International Conference on Acoustics, 2021

Solving sparse linear systems with approximate inverse preconditioners on analog devices.
Proceedings of the 2021 IEEE High Performance Extreme Computing Conference, 2021

Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments.
Proceedings of the Thinking Fast and Slow and Other Cognitive Theories in AI, 2021

Epistemic Planning in a Fast and Slow Setting.
Proceedings of the Thinking Fast and Slow and Other Cognitive Theories in AI, 2021

Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Thinking Fast and Slow in AI.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Denoising quantum states with Quantum Autoencoders - Theory and Applications.
CoRR, 2020

Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra.
CoRR, 2020

Projection techniques to update the truncated SVD of evolving matrices.
CoRR, 2020

Dynamic graph based epidemiological model for COVID-19 contact tracing data analysis and optimal testing prescription.
CoRR, 2020

Symbolic Regression using Mixed-Integer Nonlinear Optimization.
CoRR, 2020

Tensor-Tensor Products for Optimal Representation and Compression.
CoRR, 2020

2019
Communication over Continuous Quantum Secure Dialogue using Einstein-Podolsky-Rosen States.
CoRR, 2019

Tensor Graph Convolutional Networks for Prediction on Dynamic Graphs.
CoRR, 2019

Recurrent Neural Networks in the Eye of Differential Equations.
CoRR, 2019

2018
Experimental Design for Nonparametric Correction of Misspecified Dynamical Models.
SIAM/ASA J. Uncertain. Quantification, 2018

Stable Tensor Neural Networks for Rapid Deep Learning.
CoRR, 2018

2017
Image classification using local tensor singular value decompositions.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2015
Community Detection Using Time-Dependent Personalized PageRank.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Semi-discrete Matrix-Free Formulation of 3D Elastic Full Waveform Inversion Modeling.
Proceedings of the Euro-Par 2015: Parallel Processing, 2015

Source estimation for wave equations with uncertain parameters.
Proceedings of the 14th European Control Conference, 2015

2013
Improving training time of Hessian-free optimization for deep neural networks using preconditioning and sampling.
CoRR, 2013

Accelerating Hessian-free optimization for Deep Neural Networks by implicit preconditioning and sampling.
Proceedings of the 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 2013

2011
A Second Order Discretization of Maxwell's Equations in the Quasi-Static Regime on OcTree Grids.
SIAM J. Sci. Comput., 2011

2010
Kalman filtering for compressed sensing.
Proceedings of the 13th Conference on Information Fusion, 2010

2008
Use of anisotropic modelling in electrical impedance tomography; Description of method and preliminary assessment of utility in imaging brain function in the adult human head.
NeuroImage, 2008

2007
Design of electrodes and current limits for low frequency electrical impedance tomography of the brain.
Medical Biol. Eng. Comput., 2007

2005
Applications of GRID in Clinical Neurophysiology and Electrical Impedance Tomography of Brain Function.
Proceedings of the From Grid to Healthgrid, 2005


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