Sushrut Karmalkar
Sushrut Karmalkar
Verified email at cs.utexas.edu - Homepage
Title
Cited by
Cited by
Year
List-decodable linear regression
S Karmalkar, AR Klivans, PK Kothari
arXiv preprint arXiv:1905.05679, 2019
302019
Compressed sensing with adversarial sparse noise via l1 regression
S Karmalkar, E Price
arXiv preprint arXiv:1809.08055, 2018
212018
Superpolynomial lower bounds for learning one-layer neural networks using gradient descent
S Goel, A Gollakota, Z Jin, S Karmalkar, A Klivans
International Conference on Machine Learning, 3587-3596, 2020
152020
Time/accuracy tradeoffs for learning a relu with respect to gaussian marginals
S Goel, S Karmalkar, A Klivans
arXiv preprint arXiv:1911.01462, 2019
152019
Outlier-robust high-dimensional sparse estimation via iterative filtering
I Diakonikolas, S Karmalkar, D Kane, E Price, A Stewart
arXiv preprint arXiv:1911.08085, 2019
132019
Robustly learning any clusterable mixture of gaussians
I Diakonikolas, SB Hopkins, D Kane, S Karmalkar
arXiv preprint arXiv:2005.06417, 2020
122020
Approximation schemes for relu regression
I Diakonikolas, S Goel, S Karmalkar, AR Klivans, M Soltanolkotabi
Conference on Learning Theory, 1452-1485, 2020
112020
Lower bounds for compressed sensing with generative models
A Kamath, S Karmalkar, E Price
arXiv preprint arXiv:1912.02938, 2019
82019
Fourier entropy-influence conjecture for random linear threshold functions
S Chakraborty, S Karmalkar, S Kundu, SV Lokam, N Saurabh
Latin American Symposium on Theoretical Informatics, 275-289, 2018
32018
Robust polynomial regression up to the information theoretic limit
D Kane, S Karmalkar, E Price
2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017
32017
On the power of compressed sensing with generative models
A Kamath, E Price, S Karmalkar
International Conference on Machine Learning, 5101-5109, 2020
12020
Outlier-Robust Clustering of Gaussians and Other Non-Spherical Mixtures
A Bakshi, I Diakonikolas, SB Hopkins, D Kane, S Karmalkar, PK Kothari
2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020
2020
The Polynomial Method is Universal for Distribution-Free Correlational SQ Learning
A Gollakota, S Karmalkar, A Klivans
arXiv preprint arXiv:2010.11925, 2020
2020
Depth separation and weight-width trade-offs for sigmoidal neural networks
A Deshpande, N Goyal, S Karmalkar
2018
On Robust Concepts and Small Neural Nets
A Deshpande, S Karmalkar
2017
Compressed Sensing with Approximate Priors via Conditional Resampling
A Jalal, UT ECE, S Karmalkar, UT CS, AG Dimakis, E Price
Supplemental: Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent
S Goel, A Gollakota, Z Jin, S Karmalkar, A Klivans
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