Vikrant Singhal

27 papers A* 9A 1B 2Misc 1Journal 14

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	Uniformity Testing Under User-Level Local Privacy. ITCS Clément L. Canonne, Abigail Gentle, Vikrant Singhal
2025	J	`jnl`	Beyond Laplace and Gaussian: Exploring the Generalized Gaussian Mechanism for Private Machine Learning. CoRR Roy Rinberg, Ilia Shumailov, Vikrant Singhal, Rachel Cummings, Nicolas Papernot
2025	J	`jnl`	Uniformity Testing under User-Level Local Privacy. CoRR Clément L. Canonne, Abigail Gentle, Vikrant Singhal
2024	B	`conf`	A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions. ALT Vikrant Singhal
2024	B	`conf`	Not All Learnable Distribution Classes are Privately Learnable. ALT Mark Bun, Gautam Kamath, Argyris Mouzakis, Vikrant Singhal
2024	J	`jnl`	Not All Learnable Distribution Classes are Privately Learnable. CoRR Mark Bun, Gautam Kamath, Argyris Mouzakis, Vikrant Singhal
2024	J	`jnl`	Private Means and the Curious Incident of the Free Lunch. CoRR Jack Fitzsimons, James Honaker, Michael Shoemate, Vikrant Singhal
2023	J	`jnl`	A Bias-Variance-Privacy Trilemma for Statistical Estimation. CoRR Gautam Kamath, Argyris Mouzakis, Matthew Regehr, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman
2023	J	`jnl`	A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions. CoRR Vikrant Singhal
2023	A*	`conf`	Private Distribution Learning with Public Data: The View from Sample Compression. NeurIPS Shai Ben-David, Alex Bie, Clément L. Canonne, Gautam Kamath, Vikrant Singhal
2023	J	`jnl`	Private Distribution Learning with Public Data: The View from Sample Compression. CoRR Shai Ben-David, Alex Bie, Clément L. Canonne, Gautam Kamath, Vikrant Singhal
2022	A*	`conf`	A Private and Computationally-Efficient Estimator for Unbounded Gaussians. COLT Gautam Kamath, Argyris Mouzakis, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman
2022	A*	`conf`	New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma. NeurIPS Gautam Kamath, Argyris Mouzakis, Vikrant Singhal
2022	J	`jnl`	New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma. CoRR Gautam Kamath, Argyris Mouzakis, Vikrant Singhal
2022	A*	`conf`	Private Estimation with Public Data. NeurIPS Alex Bie, Gautam Kamath, Vikrant Singhal
2022	J	`jnl`	Private Estimation with Public Data. CoRR Alex Bie, Gautam Kamath, Vikrant Singhal
2021	J	`jnl`	A Private and Computationally-Efficient Estimator for Unbounded Gaussians. CoRR Gautam Kamath, Argyris Mouzakis, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman
2021	A*	`conf`	Privately Learning Subspaces. NeurIPS Vikrant Singhal, Thomas Steinke
2021	J	`jnl`	Privately Learning Subspaces. CoRR Vikrant Singhal, Thomas Steinke
2020	Misc	`conf`	Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. ITA Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman
2020	A*	`conf`	Private Mean Estimation of Heavy-Tailed Distributions. COLT Gautam Kamath, Vikrant Singhal, Jonathan R. Ullman
2020	J	`jnl`	Private Mean Estimation of Heavy-Tailed Distributions. CoRR Gautam Kamath, Vikrant Singhal, Jonathan R. Ullman
2019	A*	`conf`	Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. NeurIPS Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman
2019	J	`jnl`	Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. CoRR Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman
2019	A*	`conf`	Privately Learning High-Dimensional Distributions. COLT Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan R. Ullman
2018	J	`jnl`	Privately Learning High-Dimensional Distributions. CoRR Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan R. Ullman
2016	A*	`conf`	Deterministic and probabilistic binary search in graphs. STOC Ehsan Emamjomeh-Zadeh, David Kempe, Vikrant Singhal