Deep Neural Networks for HDR imaging. - Kshiteej Sheth (CoRR, 2016)

Deep-learnt classification of light curves. - Ashish Mahabal; Kshiteej Sheth; Fabian Gieseke; Akshay Pai; S. George Djorgovski; Andrew J. Drake; Matthew J. Graham (SSCI, 2017)

Improved linear embeddings via Lagrange duality. - Kshiteej Sheth; Dinesh Garg; Anirban Dasgupta 001 (Mach. Learn., 2019)

Towards Non-Uniform k-Center with Constant Types of Radii. - Xinrui Jia 001; Lars Rohwedder; Kshiteej Sheth; Ola Svensson (CoRR, 2021)

Towards Non-Uniform k-Center with Constant Types of Radii. - Xinrui Jia 001; Lars Rohwedder; Kshiteej Sheth; Ola Svensson (SOSA, 2022)

Fair colorful k-center clustering. - Xinrui Jia 001; Kshiteej Sheth; Ola Svensson (Math. Program., 2022)

Toeplitz Low-Rank Approximation with Sublinear Query Complexity. - Michael Kapralov; Hannah Lawrence; Mikhail Makarov; Cameron Musco; Kshiteej Sheth (SODA, 2023)

Sublinear Time Low-Rank Approximation of Toeplitz Matrices. - Cameron Musco; Kshiteej Sheth (SODA, 2024)

Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions. - Piotr Indyk; Michael Kapralov; Kshiteej Sheth; Tal Wagner (ICLR, 2025)

BalanceKV: KV Cache Compression through Discrepancy Theory. - Insu Han; Michael Kapralov; Ekaterina Kochetkova; Kshiteej Sheth; Amir Zandieh (CoRR, 2025)