Sushrut Karmalkar
16 papers · 2019–2025 · 3 venues · across top CS/AI venues
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Venues
Top co-authors
Research topics
Machine Learning
(16)
Optimization & Theory
(14)
Core Methods
(12)
Mathematics & Optimization
(10)
Optimization
(9)
Learning Types
(5)
Deep Learning
(4)
Mathematics
(4)
Models
(3)
Artificial Intelligence
(2)
Computer Science
(1)
Computer Vision
(1)
Application Areas
(1)
Bayesian & Probabilistic Β· Artificial Intelligence
(1)
Bayesian & Probabilistic Β· Machine Learning
(1)
Keywords
sparse estimation
(4)
linear regression
(3)
sparse mean estimation
(3)
statistical query
(3)
gaussian distribution
(3)
mean estimation
(3)
list-decodable learning
(3)
generative model
(3)
robust regression
(3)
compressed sensing
(2)
sample complexity
(2)
robust statistics
(2)
relu activation
(2)
square loss
(2)
learning theory
(2)
robust estimation
(2)
high-dimensional statistics
(2)
gradient descent
(2)
outlier detection
(2)
posterior sampling
(2)
Papers
Batch List-Decodable Linear Regression via Higher Moments
ICML 2025
On Learning Parallel Pancakes with Mostly Uniform Weights
ICML 2025
Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
NeurIPS 2024
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination
ICML 2024
Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions
COLT 2023
First Order Stochastic Optimization with Oblivious Noise
NeurIPS 2023
List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering
NeurIPS 2022
Robust Sparse Mean Estimation via Sum of Squares
COLT 2022
Fairness for Image Generation with Uncertain Sensitive Attributes
ICML 2021
Instance-Optimal Compressed Sensing via Posterior Sampling
ICML 2021
Approximation Schemes for ReLU Regression
COLT 2020
On the Power of Compressed Sensing with Generative Models
ICML 2020
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent
ICML 2020
List-decodable Linear Regression
NeurIPS 2019
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
NeurIPS 2019
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals
NeurIPS 2019