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10/05/2022
A Fourier Approach to Mixture Learning
We revisit the problem of learning mixtures of spherical Gaussians. Give...
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10/03/2022
Online Pen Testing
We study a "pen testing" problem, in which we are given n pens with unkn...
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06/29/2022
Open Problem: Properly learning decision trees in polynomial time?
The authors recently gave an n^O(loglog n) time membership query algorit...
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09/01/2021
Properly learning decision trees in almost polynomial time
We give an n^O(loglog n)-time membership query algorithm for properly an...
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07/02/2021
Decision tree heuristics can fail, even in the smoothed setting
Greedy decision tree learning heuristics are mainstays of machine learni...
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06/29/2021
Exponential Weights Algorithms for Selective Learning
We study the selective learning problem introduced by Qiao and Valiant (...
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12/07/2020
Stronger Calibration Lower Bounds via Sidestepping
We consider an online binary prediction setting where a forecaster obser...
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02/12/2019
A Theory of Selective Prediction
We consider a model of selective prediction, where the prediction algori...
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02/02/2019
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning
Generalization error (also known as the out-of-sample error) measures ho...
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05/12/2018
Do Outliers Ruin Collaboration?
We consider the problem of learning a binary classifier from n different...
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06/04/2017
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration
We study the combinatorial pure exploration problem Best-Set in stochast...
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05/19/2017
Practical Algorithms for Best-K Identification in Multi-Armed Bandits
In the Best-K identification problem (Best-K-Arm), we are given N stocha...
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02/13/2017
Nearly Instance Optimal Sample Complexity Bounds for Top-k Arm Selection
In the Best-k-Arm problem, we are given n stochastic bandit arms, each a...
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08/22/2016