Lior Horesh
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
20
Venues
14
Active years
2010–2025
Best venue rank
A*
Where they publish
Papers
20 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICASSP | Epigraph Based Multilevel Optimization (EMO) for Enhancing Chain-of-Thought Reasoning Capabilities. | Songtao Lu, Yanna Ding, Lior Horesh, Jianxi Gao, Malik Magdon-Ismail |
| 2025 | SC | Fast Linear Solvers via AI-Tuned Markov Chain Monte Carlo-based Matrix Inversion. | Anton Lebedev, Won Kyung Lee, Soumyadip Ghosh, Olha Ivanyshyn Yaman, Vassilis Kalantzis, Yingdong Lu, Tomasz Nowicki, Shashanka Ubaru, Lior Horesh, Vassil Alexandrov |
| 2024 | AISTATS | Asynchronous Randomized Trace Estimation. | Vasileios Kalantzis, Shashanka Ubaru, Chai Wah Wu, Georgios Kollias, Lior Horesh |
| 2024 | ICAPS | On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS). | Vishal Pallagani, Bharath C. Muppasani, Kaushik Roy, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh, Amit P. Sheth |
| 2024 | ICLR | Topological data analysis on noisy quantum computers. | Ismail Yunus Akhalwaya, Shashanka Ubaru, Kenneth L. Clarkson, Mark S. Squillante, Vishnu Jejjala, Yang-Hui He, Kugendran Naidoo, Vasileios Kalantzis, Lior Horesh |
| 2023 | IJCAI | Plansformer Tool: Demonstrating Generation of Symbolic Plans Using Transformers. | Vishal Pallagani, Bharath Muppasani, Biplav Srivastava, Francesca Rossi, Lior Horesh, Keerthiram Murugesan, Andrea Loreggia, Francesco Fabiano, Rony Joseph, Yathin Kethepalli |
| 2022 | ICASSP | Decentralized Bilevel Optimization for Personalized Client Learning. | Songtao Lu, Xiaodong Cui, Mark S. Squillante, Brian Kingsbury, Lior Horesh |
| 2022 | ICML | Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra. | Nadiia Chepurko, Kenneth L. Clarkson, Lior Horesh, Honghao Lin, David P. Woodruff |
| 2022 | NeSy | Combining Fast and Slow Thinking for Human-like and Efficient Decisions in Constrained Environments. | Marianna Bergamaschi Ganapini, Murray Campbell, Francesco Fabiano, Lior Horesh, Jonathan Lenchner, Andrea Loreggia, Nicholas Mattei, Francesca Rossi, Biplav Srivastava, K. Brent Venable |
| 2022 | UAI | Distributed adversarial training to robustify deep neural networks at scale. | Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu |
| 2021 | AAAI | Thinking Fast and Slow in AI. | Grady Booch, Francesco Fabiano, Lior Horesh, Kiran Kate, Jonathan Lenchner, Nick Linck, Andrea Loreggia, Keerthiram Murugesan, Nicholas Mattei, Francesca Rossi, Biplav Srivastava |
| 2021 | AAAI | Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning. | Songtao Lu, Kaiqing Zhang, Tianyi Chen, Tamer Basar, Lior Horesh |
| 2021 | ICASSP | Sparse Graph Based Sketching for Fast Numerical Linear Algebra. | Dong Hu, Shashanka Ubaru, Alex Gittens, Kenneth L. Clarkson, Lior Horesh, Vassilis Kalantzis |
| 2021 | ICASSP | Training Logical Neural Networks by Primal-Dual Methods for Neuro-Symbolic Reasoning. | Songtao Lu, Naweed Khan, Ismail Yunus Akhalwaya, Ryan Riegel, Lior Horesh, Alexander G. Gray |
| 2021 | ICML | Projection techniques to update the truncated SVD of evolving matrices with applications. | Vasileios Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth L. Clarkson |
| 2021 | SDM | Dynamic Graph Convolutional Networks Using the Tensor M-Product. | Osman Asif Malik, Shashanka Ubaru, Lior Horesh, Misha E. Kilmer, Haim Avron |
| 2015 | EuroPar | Semi-discrete Matrix-Free Formulation of 3D Elastic Full Waveform Inversion Modeling. | Stephen Moore, Devi Sudheer Chunduri, Sergiy Zhuk, Tigran T. Tchrakian, Ewout van den Berg, Albert Akhriev, Alberto Costa Nogueira Jr., Andrew A. Rawlinson, Lior Horesh |
| 2015 | ICML | Community Detection Using Time-Dependent Personalized PageRank. | Haim Avron, Lior Horesh |
| 2013 | ASRU | Accelerating Hessian-free optimization for Deep Neural Networks by implicit preconditioning and sampling. | Tara N. Sainath, Lior Horesh, Brian Kingsbury, Aleksandr Y. Aravkin, Bhuvana Ramabhadran |
| 2010 | FUSION | Kalman filtering for compressed sensing. | Dimitri Kanevsky, Avishy Carmi, Lior Horesh, Pini Gurfil, Bhuvana Ramabhadran, Tara N. Sainath |