Deterministic and probabilistic binary search in graphs. - Ehsan Emamjomeh-Zadeh; David Kempe 001; Vikrant Singhal (STOC, 2016)

Privately Learning High-Dimensional Distributions. - Gautam Kamath 001; Jerry Li 001; Vikrant Singhal; Jonathan R. Ullman (COLT, 2019)

Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. - Gautam Kamath 001; Or Sheffet; Vikrant Singhal; Jonathan R. Ullman (NeurIPS, 2019)

Private Mean Estimation of Heavy-Tailed Distributions. - Gautam Kamath 001; Vikrant Singhal; Jonathan R. Ullman (COLT, 2020)

Privately Learning Subspaces. - Vikrant Singhal; Thomas Steinke 002 (NeurIPS, 2021)

A Private and Computationally-Efficient Estimator for Unbounded Gaussians. - Gautam Kamath 001; Argyris Mouzakis; Vikrant Singhal; Thomas Steinke 002; Jonathan R. Ullman (COLT, 2022)

New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma. - Gautam Kamath 001; Argyris Mouzakis; Vikrant Singhal (NeurIPS, 2022)

Private Estimation with Public Data. - Alex Bie; Gautam Kamath 001; Vikrant Singhal (NeurIPS, 2022)

Private Distribution Learning with Public Data: The View from Sample Compression. - Shai Ben-David; Alex Bie; Clément L. Canonne; Gautam Kamath 001; Vikrant Singhal (NeurIPS, 2023)

A Bias-Variance-Privacy Trilemma for Statistical Estimation. - Gautam Kamath 001; Argyris Mouzakis; Matthew Regehr; Vikrant Singhal; Thomas Steinke 002; Jonathan R. Ullman (CoRR, 2023)

Not All Learnable Distribution Classes are Privately Learnable. - Mark Bun; Gautam Kamath 001; Argyris Mouzakis; Vikrant Singhal (ALT, 2024)

A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions. - Vikrant Singhal (ALT, 2024)

Private Means and the Curious Incident of the Free Lunch. - Jack Fitzsimons; James Honaker; Michael Shoemate; Vikrant Singhal (CoRR, 2024)

Beyond Laplace and Gaussian: Exploring the Generalized Gaussian Mechanism for Private Machine Learning. - Roy Rinberg; Ilia Shumailov; Vikrant Singhal; Rachel Cummings; Nicolas Papernot (CoRR, 2025)