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06/06/2023
Binary Classification with Instance and Label Dependent Label Noise
Learning with label dependent label noise has been extensively explored ...
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05/11/2023
Active Learning in the Predict-then-Optimize Framework: A Margin-Based Approach
We develop the first active learning method in the predict-then-optimize...
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06/15/2022
Online Contextual Decision-Making with a Smart Predict-then-Optimize Method
We study an online contextual decision-making problem with resource cons...
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10/24/2021
Integrated Conditional Estimation-Optimization
Many real-world optimization problems involve uncertain parameters with ...
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08/19/2021
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method
The predict-then-optimize framework is fundamental in practical stochast...
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04/20/2021
Joint Online Learning and Decision-making via Dual Mirror Descent
We consider an online revenue maximization problem over a finite time ho...
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06/09/2019
Stochastic In-Face Frank-Wolfe Methods for Non-Convex Optimization and Sparse Neural Network Training
The Frank-Wolfe method and its extensions are well-suited for delivering...
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05/27/2019
Generalization Bounds in the Predict-then-Optimize Framework
The predict-then-optimize framework is fundamental in many practical set...
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10/20/2018
Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods
Logistic regression is one of the most popular methods in binary classif...
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10/22/2017
Smart "Predict, then Optimize"
Many real-world analytics problems involve two significant challenges: p...
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11/06/2015
An Extended Frank-Wolfe Method with "In-Face" Directions, and its Application to Low-Rank Matrix Completion
Motivated principally by the low-rank matrix completion problem, we pres...
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05/16/2015
A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives
In this paper we analyze boosting algorithms in linear regression from a...
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07/04/2013