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Ensembling over Classifiers: a Bias-Variance Perspective


Jun 21, 2022
Neha Gupta, Jamie Smith, Ben Adlam, Zelda Mariet


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Understanding the bias-variance tradeoff of Bregman divergences


Feb 10, 2022
Ben Adlam, Neha Gupta, Zelda Mariet, Jamie Smith


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Estimating decision tree learnability with polylogarithmic sample complexity


Nov 03, 2020
Guy Blanc, Neha Gupta, Jane Lange, Li-Yang Tan

* 25 pages, to appear in NeurIPS 2020 

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Universal guarantees for decision tree induction via a higher-order splitting criterion


Oct 16, 2020
Guy Blanc, Neha Gupta, Jane Lange, Li-Yang Tan


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Active Local Learning


Sep 04, 2020
Arturs Backurs, Avrim Blum, Neha Gupta

* Published at COLT 2020 

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Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process


Apr 19, 2019
Guy Blanc, Neha Gupta, Gregory Valiant, Paul Valiant


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Exploiting Numerical Sparsity for Efficient Learning : Faster Eigenvector Computation and Regression


Nov 27, 2018
Neha Gupta, Aaron Sidford

* To appear in NIPS 2018 

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