Ainesh Bakshi - RankMe

59 papers A* 25A 1B 2C 1Journal 28Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Additive Approximation Schemes for Low-Dimensional Embeddings. SODA Prashanti Anderson, Ainesh Bakshi, Samuel B. Hopkins
2025	J	`jnl`	A Dobrushin condition for quantum Markov chains: Rapid mixing and conditional mutual information at high temperature. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2025	J	`jnl`	Additive Approximation Schemes for Low-Dimensional Embeddings. CoRR Prashanti Anderson, Ainesh Bakshi, Samuel B. Hopkins
2025	A*	`conf`	Learning the Closest Product State. STOC Ainesh Bakshi, John Bostanci, William Kretschmer, Zeph Landau, Jerry Li, Allen Liu, Ryan O'Donnell, Ewin Tang
2025	A*	`conf`	Metric Embeddings Beyond Bi-Lipschitz Distortion via Sherali-Adams. COLT Ainesh Bakshi, Vincent Cohen-Addad, Rajesh Jayaram, Sam Hopkins, Silvio Lattanzi
2025	A*	`conf`	Sample-Optimal Private Regression in Polynomial Time. STOC Prashanti Anderson, Ainesh Bakshi, Mahbod Majid, Stefan Tiegel
2025	J	`jnl`	Sample-Optimal Private Regression in Polynomial Time. CoRR Prashanti Anderson, Ainesh Bakshi, Mahbod Majid, Stefan Tiegel
2024	A*	`conf`	An Improved Classical Singular Value Transformation for Quantum Machine Learning. SODA Ainesh Bakshi, Ewin Tang
2024	A*	`conf`	Efficient Certificates of Anti-Concentration Beyond Gaussians. FOCS Ainesh Bakshi, Pravesh K. Kothari, Goutham Rajendran, Madhur Tulsiani, Aravindan Vijayaraghavan
2024	J	`jnl`	Efficient Certificates of Anti-Concentration Beyond Gaussians. CoRR Ainesh Bakshi, Pravesh Kothari, Goutham Rajendran, Madhur Tulsiani, Aravindan Vijayaraghavan
2024	J	`jnl`	File System Aging. CoRR Alex Conway, Ainesh Bakshi, Arghya Bhattacharya, Rory Bennett, Yizheng Jiao, Eric Knorr, Yang Zhan, Michael A. Bender, William Jannen, Rob Johnson, Bradley C. Kuszmaul, Donald E. Porter, Jun Yuan, Martin Farach-Colton
2024	A*	`conf`	High-Temperature Gibbs States are Unentangled and Efficiently Preparable. FOCS Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2024	J	`jnl`	High-Temperature Gibbs States are Unentangled and Efficiently Preparable. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2024	A*	`conf`	Learning Quantum Hamiltonians at Any Temperature in Polynomial Time. STOC Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2024	A*	`conf`	Structure Learning of Hamiltonians from Real-Time Evolution. FOCS Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2024	J	`jnl`	Structure learning of Hamiltonians from real-time evolution. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2023	J	`jnl`	A Near-Linear Time Algorithm for the Chamfer Distance. CoRR Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
2023	A*	`conf`	A New Approach to Learning Linear Dynamical Systems. STOC Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
2023	J	`jnl`	A New Approach to Learning Linear Dynamical Systems. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
2023	J	`jnl`	A quasi-polynomial time algorithm for Multi-Dimensional Scaling via LP hierarchies. CoRR Ainesh Bakshi, Vincent Cohen-Addad, Samuel B. Hopkins, Rajesh Jayaram, Silvio Lattanzi
2023	J	`jnl`	An Improved Classical Singular Value Transformation for Quantum Machine Learning. CoRR Ainesh Bakshi, Ewin Tang
2023	A*	`conf`	Krylov Methods are (nearly) Optimal for Low-Rank Approximation. FOCS Ainesh Bakshi, Shyam Narayanan
2023	J	`jnl`	Krylov Methods are (nearly) Optimal for Low-Rank Approximation. CoRR Ainesh Bakshi, Shyam Narayanan
2023	J	`jnl`	Learning quantum Hamiltonians at any temperature in polynomial time. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
2023	A*	`conf`	Near-Linear Time Algorithm for the Chamfer Distance. NeurIPS Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
2023	A*	`conf`	Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
2023	A*	`conf`	Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. ICML Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
2023	J	`jnl`	Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. CoRR Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
2022	J	`jnl`	Low-Rank Approximation with 1/ε CoRR Ainesh Bakshi, Kenneth L. Clarkson, David P. Woodruff
2022	A*	`conf`	Low-rank approximation with STOC Ainesh Bakshi, Kenneth L. Clarkson, David P. Woodruff
2022	A*	`conf`	Robustly learning mixtures of STOC Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala
2022	J	`jnl`	Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
2021	A*	`conf`	Learning a Latent Simplex in Input Sparsity Time. ICLR Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou
2021	J	`jnl`	Learning a Latent Simplex in Input-Sparsity Time. CoRR Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou
2021	A*	`conf`	List-Decodable Subspace Recovery: Dimension Independent Error in Polynomial Time. SODA Ainesh Bakshi, Pravesh K. Kothari
2021	A*	`conf`	Robust linear regression: optimal rates in polynomial time. STOC Ainesh Bakshi, Adarsh Prasad
2020	J	`jnl`	List-Decodable Subspace Recovery via Sum-of-Squares. CoRR Ainesh Bakshi, Pravesh Kothari
2020	A*	`conf`	Outlier-Robust Clustering of Gaussians and Other Non-Spherical Mixtures. FOCS Ainesh Bakshi, Ilias Diakonikolas, Samuel B. Hopkins, Daniel Kane, Sushrut Karmalkar, Pravesh K. Kothari
2020	J	`jnl`	Outlier-Robust Clustering of Non-Spherical Mixtures. CoRR Ainesh Bakshi, Pravesh Kothari
2020	J	`jnl`	Robust Linear Regression: Optimal Rates in Polynomial Time. CoRR Ainesh Bakshi, Adarsh Prasad
2020	A*	`conf`	Robust and Sample Optimal Algorithms for PSD Low Rank Approximation. FOCS Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff
2020	J	`jnl`	Robustly Learning Mixtures of k Arbitrary Gaussians. CoRR Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala
2020	A*	`conf`	Testing Positive Semi-Definiteness via Random Submatrices. FOCS Ainesh Bakshi, Nadiia Chepurko, Rajesh Jayaram
2020	J	`jnl`	Testing Positive Semi-Definiteness via Random Submatrices. CoRR Ainesh Bakshi, Nadiia Chepurko, Rajesh Jayaram
2020	—	`conf`	Weighted Maximum Independent Set of Geometric Objects in Turnstile Streams. APPROX-RANDOM Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff
2019	A*	`conf`	Learning Two Layer Rectified Neural Networks in Polynomial Time. COLT Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff
2019	A*	`conf`	Robust Communication-Optimal Distributed Clustering Algorithms. ICALP Pranjal Awasthi, Ainesh Bakshi, Maria-Florina Balcan, Colin White, David P. Woodruff
2019	J	`jnl`	Robust and Sample Optimal Algorithms for PSD Low-Rank Approximation. CoRR Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff
2019	J	`jnl`	Weighted Maximum Independent Set of Geometric Objects in Turnstile Streams. CoRR Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff
2018	J	`jnl`	Learning Two Layer Rectified Neural Networks in Polynomial Time. CoRR Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff
2018	A*	`conf`	Sublinear Time Low-Rank Approximation of Distance Matrices. NeurIPS Ainesh Bakshi, David P. Woodruff
2018	J	`jnl`	Sublinear Time Low-Rank Approximation of Distance Matrices. CoRR Ainesh Bakshi, David P. Woodruff
2017	A	`conf`	File Systems Fated for Senescence? Nonsense, Says Science! FAST Alexander Conway, Ainesh Bakshi, Yizheng Jiao, William Jannen, Yang Zhan, Jun Yuan, Michael A. Bender, Rob Johnson, Bradley C. Kuszmaul, Donald E. Porter, Martin Farach-Colton
2017	J	`jnl`	How to Fragment Your File System. login Usenix Mag. Alex Conway, Ainesh Bakshi, Yizheng Jiao, Yang Zhan, Michael A. Bender, William Jannen, Rob Johnson, Bradley C. Kuszmaul, Donald E. Porter, Jun Yuan, Martin Farach-Colton
2014	B	`conf`	A Novel Feature Selection and Extraction Technique for Classification. ICFHR Kratarth Goel, Raunaq Vohra, Ainesh Bakshi
2014	J	`jnl`	A Novel Feature Selection and Extraction Technique for Classification. CoRR Kratarth Goel, Raunaq Vohra, Ainesh Bakshi
2014	B	`conf`	A novel feature selection and extraction technique for classification. SMC Kratarth Goel, Raunaq Vohra, Ainesh Bakshi
2014	—	`conf`	Non Dominated Sorting Genetic Algorithm for Chance Constrained Supplier Selection Model with Volume Discounts. ACIIDS (2) Remica Aggarwal, Ainesh Bakshi
2013	C	`conf`	Autonomous Robot Navigation: Path Planning on a Detail-Preserving Reduced-Complexity Representation of 3D Point Clouds. ICVS Rohit Sant, Ninad Kulkarni, Ainesh Bakshi, Salil Kapur, Kratarth Goel