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07/06/2023
When Does Confidence-Based Cascade Deferral Suffice?
Cascades are a classical strategy to enable inference cost to vary adapt...
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01/29/2023
Learning to reject meets OOD detection: Are all abstentions created equal?
Learning to reject (L2R) and out-of-distribution (OOD) detection are two...
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10/18/2022
Consistent Multiclass Algorithms for Complex Metrics and Constraints
We present consistent algorithms for multiclass learning with complex pe...
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06/13/2022
Robust Distillation for Worst-class Performance
Knowledge distillation has proven to be an effective technique in improv...
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07/23/2021
Implicit Rate-Constrained Optimization of Non-decomposable Objectives
We consider a popular family of constrained optimization problems arisin...
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07/09/2021
Training Over-parameterized Models with Non-decomposable Objectives
Many modern machine learning applications come with complex and nuanced ...
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06/04/2021
Churn Reduction via Distillation
In real-world systems, models are frequently updated as more data become...
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02/18/2021
Optimizing Black-box Metrics with Iterative Example Weighting
We consider learning to optimize a classification metric defined by a bl...
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02/13/2021
Distilling Double Descent
Distillation is the technique of training a "student" model based on exa...
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11/03/2020
Quadratic Metric Elicitation with Application to Fairness
Metric elicitation is a recent framework for eliciting performance metri...
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06/23/2020
Fair Performance Metric Elicitation
What is a fair performance metric? We consider the choice of fairness me...
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02/21/2020
Robust Optimization for Fairness with Noisy Protected Groups
Many existing fairness criteria for machine learning involve equalizing ...
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02/20/2020
Optimizing Black-box Metrics with Adaptive Surrogates
We address the problem of training models with black-box and hard-to-opt...
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09/06/2019
Optimizing Generalized Rate Metrics through Game Equilibrium
We present a general framework for solving a large class of learning pro...
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06/12/2019
Pairwise Fairness for Ranking and Regression
We present pairwise metrics of fairness for ranking and regression model...
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06/12/2017
Optimal Auctions through Deep Learning
Designing an auction that maximizes expected revenue is an intricate tas...
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05/13/2016
Support Vector Algorithms for Optimizing the Partial Area Under the ROC Curve
The area under the ROC curve (AUC) is a widely used performance measure ...
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05/13/2016
Online Optimization Methods for the Quantification Problem
The estimation of class prevalence, i.e., the fraction of a population t...
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05/26/2015
Surrogate Functions for Maximizing Precision at the Top
The problem of maximizing precision at the top of a ranked list, often d...
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05/26/2015
Optimizing Non-decomposable Performance Measures: A Tale of Two Classes
Modern classification problems frequently present mild to severe label i...
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01/01/2015
Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics
We study consistency of learning algorithms for a multi-class performanc...
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10/24/2014