Robust Polynomial Regression up to the Information Theoretic Limit. - Daniel Kane 001; Sushrut Karmalkar; Eric Price 001 (FOCS, 2017)

On Robust Concepts and Small Neural Nets. - Amit Deshpande 001; Sushrut Karmalkar (ICLR (Workshop), 2017)

Depth separation and weight-width trade-offs for sigmoidal neural networks. - Amit Deshpande 001; Navin Goyal; Sushrut Karmalkar (ICLR (Workshop), 2018)

Fourier Entropy-Influence Conjecture for Random Linear Threshold Functions. - Sourav Chakraborty 001; Sushrut Karmalkar; Srijita Kundu; Satyanarayana V. Lokam; Nitin Saurabh (LATIN, 2018)

Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering. - Ilias Diakonikolas; Daniel Kane 001; Sushrut Karmalkar; Eric Price 001; Alistair Stewart (NeurIPS, 2019)

Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals. - Surbhi Goel; Sushrut Karmalkar; Adam R. Klivans (NeurIPS, 2019)

List-decodable Linear Regression. - Sushrut Karmalkar; Adam R. Klivans; Pravesh Kothari (NeurIPS, 2019)

Compressed Sensing with Adversarial Sparse Noise via L1 Regression. - Sushrut Karmalkar; Eric Price 001 (SOSA, 2019)

Lower Bounds for Compressed Sensing with Generative Models. - Akshay Kamath; Sushrut Karmalkar; Eric Price 001 (CoRR, 2019)

Approximation Schemes for ReLU Regression. - Ilias Diakonikolas; Surbhi Goel; Sushrut Karmalkar; Adam R. Klivans; Mahdi Soltanolkotabi (COLT, 2020)

Outlier-Robust Clustering of Gaussians and Other Non-Spherical Mixtures. - Ainesh Bakshi; Ilias Diakonikolas; Samuel B. Hopkins 001; Daniel Kane 001; Sushrut Karmalkar; Pravesh K. Kothari (FOCS, 2020)

Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent. - Surbhi Goel; Aravind Gollakota; Zhihan Jin; Sushrut Karmalkar; Adam R. Klivans (ICML, 2020)

On the Power of Compressed Sensing with Generative Models. - Akshay Kamath; Eric Price 001; Sushrut Karmalkar (ICML, 2020)

Robustly Learning any Clusterable Mixture of Gaussians. - Ilias Diakonikolas; Samuel B. Hopkins 001; Daniel Kane 001; Sushrut Karmalkar (CoRR, 2020)

The Polynomial Method is Universal for Distribution-Free Correlational SQ Learning. - Aravind Gollakota; Sushrut Karmalkar; Adam R. Klivans (CoRR, 2020)

Instance-Optimal Compressed Sensing via Posterior Sampling. - Ajil Jalal; Sushrut Karmalkar; Alex Dimakis; Eric Price 001 (ICML, 2021)

Fairness for Image Generation with Uncertain Sensitive Attributes. - Ajil Jalal; Sushrut Karmalkar; Jessica Hoffmann; Alex Dimakis; Eric Price 001 (ICML, 2021)

Robust Sparse Mean Estimation via Sum of Squares. - Ilias Diakonikolas; Daniel M. Kane; Sushrut Karmalkar; Ankit Pensia; Thanasis Pittas (COLT, 2022)

List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering. - Ilias Diakonikolas; Daniel Kane 001; Sushrut Karmalkar; Ankit Pensia; Thanasis Pittas (NeurIPS, 2022)

Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions. - Ilias Diakonikolas; Sushrut Karmalkar; Jongho Park 004; Christos Tzamos (COLT, 2023)

First Order Stochastic Optimization with Oblivious Noise. - Ilias Diakonikolas; Sushrut Karmalkar; Jongho Park 004; Christos Tzamos (NeurIPS, 2023)

Sum-of-Squares Lower Bounds for Non-Gaussian Component Analysis. - Ilias Diakonikolas; Sushrut Karmalkar; Shuo Pang 002; Aaron Potechin (FOCS, 2024)

Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination. - Ilias Diakonikolas; Daniel Kane 001; Sushrut Karmalkar; Ankit Pensia; Thanasis Pittas (ICML, 2024)

Multi-Model 3D Registration: Finding Multiple Moving Objects in Cluttered Point Clouds. - David Jin; Sushrut Karmalkar; Harry Zhang; Luca Carlone (ICRA, 2024)

Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise. - Shuyao Li 001; Sushrut Karmalkar; Ilias Diakonikolas; Jelena Diakonikolas (NeurIPS, 2024)

Batch List-Decodable Linear Regression via Higher Moments. - Ilias Diakonikolas; Daniel M. Kane; Sushrut Karmalkar; Sihan Liu; Thanasis Pittas (CoRR, 2025)

Efficient Knowledge Distillation via Curriculum Extraction. - Shivam Gupta; Sushrut Karmalkar (CoRR, 2025)

On Learning Parallel Pancakes with Mostly Uniform Weights. - Ilias Diakonikolas; Daniel M. Kane; Sushrut Karmalkar; Jasper C. H. Lee; Thanasis Pittas (CoRR, 2025)

A Fourier Space Perspective on Diffusion Models. - Fabian Falck; Teodora Pandeva; Kiarash Zahirnia; Rachel Lawrence; Richard E. Turner; Edward Meeds; Javier Zazo; Sushrut Karmalkar (CoRR, 2025)