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07/07/2023
Scalable Membership Inference Attacks via Quantile Regression
Membership inference attacks are designed to determine, using black box ...
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05/31/2023
Doubly Constrained Fair Clustering
The remarkable attention which fair clustering has received in the last ...
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09/15/2022
Multicalibrated Regression for Downstream Fairness
We show how to take a regression function f̂ that is appropriately “mult...
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07/07/2022
Individual Preference Stability for Clustering
In this paper, we propose a natural notion of individual preference (IP)...
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06/22/2022
Active Learning with Safety Constraints
Active learning methods have shown great promise in reducing the number ...
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06/06/2022
Multi-learner risk reduction under endogenous participation dynamics
Prediction systems face exogenous and endogenous distribution shift – th...
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05/25/2022
Preference Dynamics Under Personalized Recommendations
Many projects (both practical and academic) have designed algorithms to ...
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02/11/2022
Distributionally Robust Data Join
Suppose we are given two datasets: a labeled dataset and unlabeled datas...
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02/04/2022
Optimal Spend Rate Estimation and Pacing for Ad Campaigns with Budgets
Online ad platforms offer budget management tools for advertisers that a...
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08/27/2021
Auctions and Prediction Markets for Scientific Peer Review
Peer reviewed publications are considered the gold standard in certifyin...
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02/16/2021
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information
Training and evaluation of fair classifiers is a challenging problem. Th...
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09/29/2020
Competition Alleviates Present Bias in Task Completion
We build upon recent work [Kleinberg and Oren, 2014, Kleinberg et al., 2...
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06/11/2020
Adaptive Sampling to Reduce Disparate Performance
Existing methods for reducing disparate performance of a classifier acro...
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06/08/2020
A Notion of Individual Fairness for Clustering
A common distinction in fair machine learning, in particular in fair cla...
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02/09/2020
Diversity and Inclusion Metrics in Subset Selection
The ethical concept of fairness has recently been applied in machine lea...
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06/07/2019
Effectiveness of Equalized Odds for Fair Classification under Imperfect Group Information
Most approaches for ensuring or improving a model's fairness with respec...
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06/01/2019
Network Formation under Random Attack and Probabilistic Spread
We study a network formation game where agents receive benefits by formi...
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04/10/2019
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
The growing capability and accessibility of machine learning has led to ...
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02/28/2019
Fair Dimensionality Reduction and Iterative Rounding for SDPs
We model "fair" dimensionality reduction as an optimization problem. A c...
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02/21/2019
Predictive Inequity in Object Detection
In this work, we investigate whether state-of-the-art object detection s...
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01/24/2019
Guarantees for Spectral Clustering with Fairness Constraints
Given the widespread popularity of spectral clustering (SC) for partitio...
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01/24/2019
Fair k-Center Clustering for Data Summarization
In data summarization we want to choose k prototypes in order to summari...
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10/31/2018
The Price of Fair PCA: One Extra Dimension
We investigate whether the standard dimensionality reduction technique o...
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03/23/2018
Datasheets for Datasets
Currently there is no standard way to identify how a dataset was created...
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01/10/2018
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
Bandit learning is characterized by the tension between long-term explor...
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06/07/2017
A Convex Framework for Fair Regression
We introduce a flexible family of fairness regularizers for (linear and ...
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05/23/2016