Adarsh Prasad

According to our database, Adarsh Prasad authored at least 18 papers between 2014 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Towards Robust and Resilient Machine Learning.

Adarsh Prasad

PhD thesis, 2022

Heavy-tailed Streaming Statistical Estimation.

Che-Ping Tsai, Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Robust linear regression: optimal rates in polynomial time.

Ainesh Bakshi, Adarsh Prasad

Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

On Proximal Policy Optimization's Heavy-tailed Gradients.

Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Zachary C. Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Learning Minimax Estimators via Online Learning.

Kartik Gupta, Arun Sai Suggala, Adarsh Prasad, Praneeth Netrapalli, Pradeep Ravikumar

CoRR, 2020

On Learning Ising Models under Huber's Contamination Model.

Adarsh Prasad, Vishwak Srinivasan, Sivaraman Balakrishnan, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Uniform Convergence of Rank-weighted Learning.

Justin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar

Proceedings of the 37th International Conference on Machine Learning, 2020

A Robust Univariate Mean Estimator is All You Need.

Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

A Unified Approach to Robust Mean Estimation.

Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

CoRR, 2019

On Human-Aligned Risk Minimization.

Liu Leqi, Adarsh Prasad, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Revisiting Adversarial Risk.

Arun Sai Suggala, Adarsh Prasad, Vaishnavh Nagarajan, Pradeep Ravikumar

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

On Adversarial Risk and Training.

Arun Sai Suggala, Adarsh Prasad, Vaishnavh Nagarajan, Pradeep Ravikumar

CoRR, 2018

Robust Estimation via Robust Gradient Estimation.

Adarsh Prasad, Arun Sai Suggala, Sivaraman Balakrishnan, Pradeep Ravikumar

CoRR, 2018

Connecting Optimization and Regularization Paths.

Arun Sai Suggala, Adarsh Prasad, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models.

Adarsh Prasad, Alexandru Niculescu-Mizil, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2015

Fast Classification Rates for High-dimensional Gaussian Generative Models.

Tianyang Li, Adarsh Prasad, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Distributional Rank Aggregation, and an Axiomatic Analysis.

Adarsh Prasad, Harsh H. Pareek, Pradeep Ravikumar

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets.

Adarsh Prasad, Stefanie Jegelka, Dhruv Batra

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014