Alina Beygelzimer

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Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)

One of the challenges in machine learning research is to ensure that pre...
03/27/2020 ∙ by Joelle Pineau, et al. ∙ 0 ∙ share

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Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case

We study the problem of efficient online multiclass linear classificatio...
02/06/2019 ∙ by Alina Beygelzimer, et al. ∙ 0 ∙ share

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Contextual Memory Trees

We design and study a Contextual Memory Tree (CMT), a learning memory co...
07/17/2018 ∙ by Wen Sun, et al. ∙ 6 ∙ share

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A Reductions Approach to Fair Classification

We present a systematic approach for achieving fairness in a binary clas...
03/06/2018 ∙ by Alekh Agarwal, et al. ∙ 0 ∙ share

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Efficient Online Bandit Multiclass Learning with Õ(√(T)) Regret

We present an efficient second-order algorithm with Õ(1/η√(T)) regret fo...
02/25/2017 ∙ by Alina Beygelzimer, et al. ∙ 0 ∙ share

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Search Improves Label for Active Learning

We investigate active learning with access to two distinct oracles: Labe...
02/23/2016 ∙ by Alina Beygelzimer, et al. ∙ 0 ∙ share

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Scalable Nonlinear Learning with Adaptive Polynomial Expansions

Can we effectively learn a nonlinear representation in time comparable t...
10/02/2014 ∙ by Alekh Agarwal, et al. ∙ 0 ∙ share

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Conditional Probability Tree Estimation Analysis and Algorithms

We consider the problem of estimating the conditional probability of a l...
08/09/2014 ∙ by Alina Beygelzimer, et al. ∙ 0 ∙ share

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Efficient Test Selection in Active Diagnosis via Entropy Approximation

We consider the problem of diagnosing faults in a system represented by ...
07/04/2012 ∙ by Alice X. Zheng, et al. ∙ 0 ∙ share

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Learning Performance of Prediction Markets with Kelly Bettors

In evaluating prediction markets (and other crowd-prediction mechanisms)...
01/31/2012 ∙ by Alina Beygelzimer, et al. ∙ 0 ∙ share

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Alina Beygelzimer

Featured Co-authors

Joelle Pineau

Hugo Larochelle

Daniel Hsu

Alekh Agarwal

John Langford

Hal Daumé III

Wen Sun

Hanna Wallach

Irina Rish

Matus Telgarsky

Miroslav Dudík

Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)

Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case

Contextual Memory Trees

A Reductions Approach to Fair Classification

Efficient Online Bandit Multiclass Learning with Õ(√(T)) Regret

Search Improves Label for Active Learning

Scalable Nonlinear Learning with Adaptive Polynomial Expansions

Conditional Probability Tree Estimation Analysis and Algorithms

Efficient Test Selection in Active Diagnosis via Entropy Approximation

Learning Performance of Prediction Markets with Kelly Bettors