Sledovat
Adarsh Prasad
Adarsh Prasad
PhD Student, Machine Learning Department, Carnegie Mellon University
E-mailová adresa ověřena na: andrew.cmu.edu - Domovská stránka
Název
Citace
Citace
Rok
Robust estimation via robust gradient estimation
A Prasad, AS Suggala, S Balakrishnan, P Ravikumar
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020
2352020
Submodular meets structured: Finding diverse subsets in exponentially-large structured item sets
A Prasad, S Jegelka, D Batra
Advances in Neural Information Processing Systems 27, 2014
882014
Robust linear regression: Optimal rates in polynomial time
A Bakshi, A Prasad
Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021
602021
Connecting optimization and regularization paths
A Suggala, A Prasad, PK Ravikumar
Advances in Neural Information Processing Systems 31, 2018
572018
Revisiting adversarial risk
AS Suggala, A Prasad, V Nagarajan, P Ravikumar
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
37*2019
A unified approach to robust mean estimation
A Prasad, S Balakrishnan, P Ravikumar
arXiv preprint arXiv:1907.00927, 2019
352019
A robust univariate mean estimator is all you need
A Prasad, S Balakrishnan, P Ravikumar
International Conference on Artificial Intelligence and Statistics, 4034-4044, 2020
222020
Uniform convergence of rank-weighted learning
J Khim, L Leqi, A Prasad, P Ravikumar
International Conference on Machine Learning, 5254-5263, 2020
212020
On human-aligned risk minimization
L Leqi, A Prasad, PK Ravikumar
Advances in Neural Information Processing Systems 32, 2019
202019
On learning ising models under huber's contamination model
A Prasad, V Srinivasan, S Balakrishnan, P Ravikumar
Advances in neural information processing systems 33, 16327-16338, 2020
182020
Studies on some biochemical constituents of blood in Ongole cows.
DG Rao, ABA Prasad, VJ Krishna, KS Rao
161981
Distributional rank aggregation, and an axiomatic analysis
A Prasad, H Pareek, P Ravikumar
International Conference on Machine Learning, 2104-2112, 2015
142015
Fast classification rates for high-dimensional gaussian generative models
T Li, A Prasad, PK Ravikumar
Advances in Neural Information Processing Systems 28, 2015
112015
On proximal policy optimization’s heavy-tailed gradients
S Garg, J Zhanson, E Parisotto, A Prasad, Z Kolter, Z Lipton, ...
International Conference on Machine Learning, 3610-3619, 2021
102021
Heavy-tailed streaming statistical estimation
CP Tsai, A Prasad, S Balakrishnan, P Ravikumar
International Conference on Artificial Intelligence and Statistics, 1251-1282, 2022
92022
On separability of loss functions, and revisiting discriminative vs generative models
A Prasad, A Niculescu-Mizil, PK Ravikumar
Advances in Neural Information Processing Systems 30, 2017
62017
Learning minimax estimators via online learning
K Gupta, AS Suggala, A Prasad, P Netrapalli, P Ravikumar
arXiv preprint arXiv:2006.11430, 2020
32020
Efficient Estimators for Heavy-Tailed Machine Learning
V Srinivasan, A Prasad, S Balakrishnan, PK Ravikumar
22020
Towards Robust and Resilient Machine Learning
A Prasad
Carnegie Mellon University, 2022
12022
Learning Minimax Estimators via Online Learning
AS Suggala, K Gupta, A Prasad, P Ravikumar
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Články 1–20