Sushrut Karmalkar

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 37

Top Topics

Generalized Linear Models

Compressed Sensing

Sensitive Attributes

Top Venues

Publications

David Jin, Sushrut Karmalkar, Harry Zhang, Luca Carlone
Multi-Model 3D Registration: Finding Multiple Moving Objects in Cluttered Point Clouds. CoRR (2024)
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination. CoRR (2024)
David Jin, Sushrut Karmalkar, Harry Zhang, Luca Carlone
Multi-Model 3D Registration: Finding Multiple Moving Objects in Cluttered Point Clouds. ICRA (2024)
Ilias Diakonikolas, Sushrut Karmalkar, Jong Ho Park, Christos Tzamos
Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions. CoRR (2023)
Ilias Diakonikolas, Sushrut Karmalkar, Jong Ho Park, Christos Tzamos
First Order Stochastic Optimization with Oblivious Noise. NeurIPS (2023)
Ilias Diakonikolas, Sushrut Karmalkar, Jong Ho Park, Christos Tzamos
Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions. COLT (2023)
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
Robust Sparse Mean Estimation via Sum of Squares. CoRR (2022)
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering. CoRR (2022)
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering. NeurIPS (2022)
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
Robust Sparse Mean Estimation via Sum of Squares. COLT (2022)
Ajil Jalal, Sushrut Karmalkar, Alexandros G. Dimakis, Eric Price
Instance-Optimal Compressed Sensing via Posterior Sampling. CoRR (2021)
Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price
Fairness for Image Generation with Uncertain Sensitive Attributes. ICML (2021)
Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price
Instance-Optimal Compressed Sensing via Posterior Sampling. ICML (2021)
Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alexandros G. Dimakis, Eric Price
Fairness for Image Generation with Uncertain Sensitive Attributes. CoRR (2021)
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)
Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi
Approximation Schemes for ReLU Regression. CoRR (2020)
Akshay Kamath, Eric Price, Sushrut Karmalkar
On the Power of Compressed Sensing with Generative Models. ICML (2020)
Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam R. Klivans
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent. ICML (2020)
Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi
Approximation Schemes for ReLU Regression. COLT (2020)
Ilias Diakonikolas, Samuel B. Hopkins, Daniel Kane, Sushrut Karmalkar
Robustly Learning any Clusterable Mixture of Gaussians. CoRR (2020)
Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam R. Klivans
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent. CoRR (2020)
Aravind Gollakota, Sushrut Karmalkar, Adam R. Klivans
The Polynomial Method is Universal for Distribution-Free Correlational SQ Learning. CoRR (2020)
Sushrut Karmalkar, Eric Price
Compressed Sensing with Adversarial Sparse Noise via L1 Regression. SOSA (2019)
Akshay Kamath, Sushrut Karmalkar, Eric Price
Lower Bounds for Compressed Sensing with Generative Models. CoRR (2019)
Sushrut Karmalkar, Adam R. Klivans, Pravesh Kothari
List-decodable Linear Regression. NeurIPS (2019)
Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals. CoRR (2019)
Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals. NeurIPS (2019)
Sushrut Karmalkar, Adam R. Klivans, Pravesh K. Kothari
List-Decodable Linear Regression. CoRR (2019)
Ilias Diakonikolas, Sushrut Karmalkar, Daniel Kane, Eric Price, Alistair Stewart
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering. CoRR (2019)
Sourav Chakraborty, Sushrut Karmalkar, Srijita Kundu, Satyanarayana V. Lokam, Nitin Saurabh
Fourier Entropy-Influence Conjecture for Random Linear Threshold Functions. CoRR (2019)
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Eric Price, Alistair Stewart
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering. NeurIPS (2019)
Amit Deshpande, Navin Goyal, Sushrut Karmalkar
Depth separation and weight-width trade-offs for sigmoidal neural networks. ICLR (Workshop) (2018)
Sushrut Karmalkar, Eric Price
Compressed Sensing with Adversarial Sparse Noise via L1 Regression. CoRR (2018)
Sourav Chakraborty, Sushrut Karmalkar, Srijita Kundu, Satyanarayana V. Lokam, Nitin Saurabh
Fourier Entropy-Influence Conjecture for Random Linear Threshold Functions. LATIN (2018)
Daniel Kane, Sushrut Karmalkar, Eric Price
Robust Polynomial Regression up to the Information Theoretic Limit. FOCS (2017)
Amit Deshpande, Sushrut Karmalkar
On Robust Concepts and Small Neural Nets. ICLR (Workshop) (2017)
Daniel M. Kane, Sushrut Karmalkar, Eric Price
Robust polynomial regression up to the information theoretic limit. CoRR (2017)