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ORCIDAdarsh Prasad
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2020 – today
- 2022
[b1]Adarsh Prasad:
Towards Robust and Resilient Machine Learning. Carnegie Mellon University, USA, 2022- [c13]Che-Ping Tsai, Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar:
Heavy-tailed Streaming Statistical Estimation. AISTATS 2022: 1251-1282 - 2021
- [c12]Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Zachary C. Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar:
On Proximal Policy Optimization's Heavy-tailed Gradients. ICML 2021: 3610-3619 - [c11]Ainesh Bakshi, Adarsh Prasad:
Robust linear regression: optimal rates in polynomial time. STOC 2021: 102-115 - [i8]Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Sivaraman Balakrishnan, Zachary C. Lipton, Ruslan Salakhutdinov, Pradeep Ravikumar:
On Proximal Policy Optimization's Heavy-tailed Gradients. CoRR abs/2102.10264 (2021) - [i7]Che-Ping Tsai, Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar:
Heavy-tailed Streaming Statistical Estimation. CoRR abs/2108.11483 (2021) - 2020
- [c10]Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar:
A Robust Univariate Mean Estimator is All You Need. AISTATS 2020: 4034-4044 - [c9]Justin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar:
Uniform Convergence of Rank-weighted Learning. ICML 2020: 5254-5263 - [c8]Adarsh Prasad, Vishwak Srinivasan, Sivaraman Balakrishnan, Pradeep Ravikumar:
On Learning Ising Models under Huber's Contamination Model. NeurIPS 2020 - [i6]Kartik Gupta, Arun Sai Suggala, Adarsh Prasad, Praneeth Netrapalli, Pradeep Ravikumar:
Learning Minimax Estimators via Online Learning. CoRR abs/2006.11430 (2020) - [i5]Ainesh Bakshi, Adarsh Prasad:
Robust Linear Regression: Optimal Rates in Polynomial Time. CoRR abs/2007.01394 (2020)
2010 – 2019
- 2019
- [c7]Arun Sai Suggala, Adarsh Prasad, Vaishnavh Nagarajan, Pradeep Ravikumar:
Revisiting Adversarial Risk. AISTATS 2019: 2331-2339 - [c6]Liu Leqi, Adarsh Prasad, Pradeep Ravikumar:
On Human-Aligned Risk Minimization. NeurIPS 2019: 15029-15038 - [i4]Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar:
A Unified Approach to Robust Mean Estimation. CoRR abs/1907.00927 (2019) - 2018
- [c5]Arun Sai Suggala, Adarsh Prasad, Pradeep Ravikumar:
Connecting Optimization and Regularization Paths. NeurIPS 2018: 10631-10641 - [i3]Adarsh Prasad, Arun Sai Suggala, Sivaraman Balakrishnan, Pradeep Ravikumar:
Robust Estimation via Robust Gradient Estimation. CoRR abs/1802.06485 (2018) - [i2]Arun Sai Suggala, Adarsh Prasad, Vaishnavh Nagarajan, Pradeep Ravikumar:
On Adversarial Risk and Training. CoRR abs/1806.02924 (2018) - 2017
- [c4]Adarsh Prasad, Alexandru Niculescu-Mizil, Pradeep Ravikumar:
On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models. NIPS 2017: 7050-7059 - 2015
- [c3]Adarsh Prasad, Harsh H. Pareek, Pradeep Ravikumar:
Distributional Rank Aggregation, and an Axiomatic Analysis. ICML 2015: 2104-2112 - [c2]Tianyang Li, Adarsh Prasad, Pradeep Ravikumar:
Fast Classification Rates for High-dimensional Gaussian Generative Models. NIPS 2015: 1054-1062 - 2014
- [c1]Adarsh Prasad, Stefanie Jegelka, Dhruv Batra:
Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets. NIPS 2014: 2645-2653 - [i1]Adarsh Prasad, Stefanie Jegelka, Dhruv Batra:
Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets. CoRR abs/1411.1752 (2014)
Coauthor Index
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