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Abhimanyu Das

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Efficient List-Decodable Regression using Batches

Nov 23, 2022
Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen

* First draft

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Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models

Jun 09, 2022
Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das

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Leveraging Initial Hints for Free in Stochastic Linear Bandits

Mar 08, 2022
Ashok Cutkosky, Chris Dann, Abhimanyu Das, Qiuyi, Zhang

* ALT 2022

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On the benefits of maximum likelihood estimation for Regression and Forecasting

Jun 18, 2021
Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh

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One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks

Mar 29, 2021
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang

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* 30 pages, 6 figures

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Upper Confidence Bounds for Combining Stochastic Bandits

Dec 24, 2020
Ashok Cutkosky, Abhimanyu Das, Manish Purohit

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Learning the gravitational force law and other analytic functions

May 15, 2020
Atish Agarwala, Abhimanyu Das, Rina Panigrahy, Qiuyi Zhang

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On the Learnability of Deep Random Networks

Apr 08, 2019
Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy

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