Ainesh Bakshi

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 44

Top Topics

Chamfer Distance

Density Estimation

Dynamical Systems

Top Venues

Publications

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
File System Aging. CoRR (2024)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
Structure learning of Hamiltonians from real-time evolution. CoRR (2024)
Ainesh Bakshi, Pravesh Kothari, Goutham Rajendran, Madhur Tulsiani, Aravindan Vijayaraghavan
Efficient Certificates of Anti-Concentration Beyond Gaussians. CoRR (2024)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
Learning Quantum Hamiltonians at Any Temperature in Polynomial Time. STOC (2024)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
High-Temperature Gibbs States are Unentangled and Efficiently Preparable. CoRR (2024)
Ainesh Bakshi, Ewin Tang
An Improved Classical Singular Value Transformation for Quantum Machine Learning. SODA (2024)
Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
Near-Linear Time Algorithm for the Chamfer Distance. NeurIPS (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. CoRR (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
A New Approach to Learning Linear Dynamical Systems. CoRR (2023)
Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
A Near-Linear Time Algorithm for the Chamfer Distance. CoRR (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
Learning quantum Hamiltonians at any temperature in polynomial time. CoRR (2023)
Ainesh Bakshi, Ewin Tang
An Improved Classical Singular Value Transformation for Quantum Machine Learning. CoRR (2023)
Ainesh Bakshi, Vincent Cohen-Addad, Samuel B. Hopkins, Rajesh Jayaram, Silvio Lattanzi
A quasi-polynomial time algorithm for Multi-Dimensional Scaling via LP hierarchies. CoRR (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. ICML (2023)
Ainesh Bakshi, Shyam Narayanan
Krylov Methods are (nearly) Optimal for Low-Rank Approximation. CoRR (2023)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR (2023)
Ainesh Bakshi, Shyam Narayanan
Krylov Methods are (nearly) Optimal for Low-Rank Approximation. FOCS (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
A New Approach to Learning Linear Dynamical Systems. STOC (2023)
Ainesh Bakshi, Kenneth L. Clarkson, David P. Woodruff
Matrix-Vector Products. CoRR (2022)
Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala
arbitrary Gaussians. STOC (2022)
Ainesh Bakshi, Kenneth L. Clarkson, David P. Woodruff
matrix-vector products. STOC (2022)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR (2022)
Ainesh Bakshi, Adarsh Prasad
Robust linear regression: optimal rates in polynomial time. STOC (2021)
Ainesh Bakshi, Pravesh K. Kothari
List-Decodable Subspace Recovery: Dimension Independent Error in Polynomial Time. SODA (2021)
Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou
Learning a Latent Simplex in Input-Sparsity Time. CoRR (2021)
Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou
Learning a Latent Simplex in Input Sparsity Time. ICLR (2021)
Ainesh Bakshi, Pravesh Kothari
Outlier-Robust Clustering of Non-Spherical Mixtures. CoRR (2020)
Ainesh Bakshi, Ilias Diakonikolas, Samuel B. Hopkins, Daniel Kane, Sushrut Karmalkar, Pravesh K. Kothari
Outlier-Robust Clustering of Gaussians and Other Non-Spherical Mixtures. FOCS (2020)
Ainesh Bakshi, Pravesh Kothari
List-Decodable Subspace Recovery via Sum-of-Squares. CoRR (2020)
Ainesh Bakshi, Adarsh Prasad
Robust Linear Regression: Optimal Rates in Polynomial Time. CoRR (2020)
Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala
Robustly Learning Mixtures of k Arbitrary Gaussians. CoRR (2020)
Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff
Weighted Maximum Independent Set of Geometric Objects in Turnstile Streams. APPROX-RANDOM (2020)
Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff
Robust and Sample Optimal Algorithms for PSD Low Rank Approximation. FOCS (2020)
Ainesh Bakshi, Nadiia Chepurko, Rajesh Jayaram
Testing Positive Semi-Definiteness via Random Submatrices. CoRR (2020)
Ainesh Bakshi, Nadiia Chepurko, Rajesh Jayaram
Testing Positive Semi-Definiteness via Random Submatrices. FOCS (2020)
Pranjal Awasthi, Ainesh Bakshi, Maria-Florina Balcan, Colin White, David P. Woodruff
Robust Communication-Optimal Distributed Clustering Algorithms. ICALP (2019)
Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff
Weighted Maximum Independent Set of Geometric Objects in Turnstile Streams. CoRR (2019)
Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff
Learning Two Layer Rectified Neural Networks in Polynomial Time. COLT (2019)
Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff
Robust and Sample Optimal Algorithms for PSD Low-Rank Approximation. CoRR (2019)
Ainesh Bakshi, David P. Woodruff
Sublinear Time Low-Rank Approximation of Distance Matrices. NeurIPS (2018)
Ainesh Bakshi, David P. Woodruff
Sublinear Time Low-Rank Approximation of Distance Matrices. CoRR (2018)
Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff
Learning Two Layer Rectified Neural Networks in Polynomial Time. CoRR (2018)
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
File Systems Fated for Senescence? Nonsense, Says Science! FAST (2017)
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
How to Fragment Your File System. login Usenix Mag. 42 (2) (2017)
Kratarth Goel, Raunaq Vohra, Ainesh Bakshi
A novel feature selection and extraction technique for classification. SMC (2014)
Remica Aggarwal, Ainesh Bakshi
Non Dominated Sorting Genetic Algorithm for Chance Constrained Supplier Selection Model with Volume Discounts. ACIIDS (2) (2014)
Kratarth Goel, Raunaq Vohra, Ainesh Bakshi
A Novel Feature Selection and Extraction Technique for Classification. CoRR (2014)
Kratarth Goel, Raunaq Vohra, Ainesh Bakshi
A Novel Feature Selection and Extraction Technique for Classification. ICFHR (2014)
Rohit Sant, Ninad Kulkarni, Ainesh Bakshi, Salil Kapur, Kratarth Goel
Autonomous Robot Navigation: Path Planning on a Detail-Preserving Reduced-Complexity Representation of 3D Point Clouds. ICVS (2013)