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Publication search results
found 76 matches
- 2024
- Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala:
Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier. COLT 2024: 1796-1881 - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps. COLT 2024: 2840-2886 - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps. CoRR abs/2402.15409 (2024) - Khashayar Gatmiry, Jonathan A. Kelner, Holden Lee:
Learning Mixtures of Gaussians Using Diffusion Models. CoRR abs/2404.18869 (2024) - 2023
- Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Sparse Recovery in Nearly-Linear Time. COLT 2023: 2352-2398 - Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Matrix Completion in Almost-Verification Time. FOCS 2023: 2102-2128 - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Feature Adaptation for Sparse Linear Regression. NeurIPS 2023 - Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala:
Sampling with Barriers: Faster Mixing via Lewis Weights. CoRR abs/2303.00480 (2023) - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Feature Adaptation for Sparse Linear Regression. CoRR abs/2305.16892 (2023) - Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Matrix Completion in Almost-Verification Time. CoRR abs/2308.03661 (2023) - 2022
- Jonathan A. Kelner, Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant, Honglin Yuan:
Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales. COLT 2022: 2431-2540 - Khashayar Gatmiry, Stefanie Jegelka, Jonathan A. Kelner:
Optimization and Adaptive Generalization of Three layer Neural Networks. ICLR 2022 - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs. NeurIPS 2022 - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
Distributional Hardness Against Preconditioned Lasso via Erasure-Robust Designs. CoRR abs/2203.02824 (2022) - Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Sparse Recovery in Nearly-Linear Time. CoRR abs/2203.04002 (2022) - 2021
- Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
On the Power of Preconditioning in Sparse Linear Regression. FOCS 2021: 550-561 - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi:
On the Power of Preconditioning in Sparse Linear Regression. CoRR abs/2106.09207 (2021) - Jonathan A. Kelner, Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant, Honglin Yuan:
Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales. CoRR abs/2111.03137 (2021) - 2020
- AmirMahdi Ahmadinejad, Jonathan A. Kelner, Jack Murtagh, John Peebles, Aaron Sidford, Salil P. Vadhan:
High-precision Estimation of Random Walks in Small Space. FOCS 2020: 1295-1306 - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra:
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds. NeurIPS 2020 - 2019
- Boaz Barak, Samuel B. Hopkins, Jonathan A. Kelner, Pravesh K. Kothari, Ankur Moitra, Aaron Potechin:
A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem. SIAM J. Comput. 48(2): 687-735 (2019) - Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra:
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds. CoRR abs/1905.01282 (2019) - AmirMahdi Ahmadinejad, Jonathan A. Kelner, Jack Murtagh, John Peebles, Aaron Sidford, Salil P. Vadhan:
High-precision Estimation of Random Walks in Small Space. CoRR abs/1912.04524 (2019) - 2018
- Michael B. Cohen, Jonathan A. Kelner, Rasmus Kyng, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford:
Solving Directed Laplacian Systems in Nearly-Linear Time through Sparse LU Factorizations. FOCS 2018: 898-909 - Michael B. Cohen, Jonathan A. Kelner, Rasmus Kyng, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford:
Solving Directed Laplacian Systems in Nearly-Linear Time through Sparse LU Factorizations. CoRR abs/1811.10722 (2018) - 2017
- Keren Censor-Hillel, Bernhard Haeupler, Jonathan A. Kelner, Petar Maymounkov:
Rumor Spreading with No Dependence on Conductance. SIAM J. Comput. 46(1): 58-79 (2017) - Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford, Adrian Vladu:
Almost-linear-time algorithms for Markov chains and new spectral primitives for directed graphs. STOC 2017: 410-419 - 2016
- Boaz Barak, Samuel B. Hopkins, Jonathan A. Kelner, Pravesh Kothari, Ankur Moitra, Aaron Potechin:
A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem. FOCS 2016: 428-437 - Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Aaron Sidford, Adrian Vladu:
Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More. FOCS 2016: 583-592 - Boaz Barak, Samuel B. Hopkins, Jonathan A. Kelner, Pravesh Kothari, Ankur Moitra, Aaron Potechin:
A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem. CoRR abs/1604.03084 (2016)
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