L. Elisa Celis | DeepAI

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∙ 06/16/2023

Subset Selection Based On Multiple Rankings in the Presence of Bias: Effectiveness of Fairness Constraints for Multiwinner Voting Score Functions

We consider the problem of subset selection where one is given multiple ...

0 Niclas Boehmer, et al. ∙

∙ 05/31/2023

Designing Closed-Loop Models for Task Allocation

Automatically assigning tasks to people is challenging because human per...

0 Vijay Keswani, et al. ∙

∙ 05/30/2022

Diverse Representation via Computational Participatory Elections – Lessons from a Case Study

Elections are the central institution of democratic processes, and often...

0 Florian Evéquoz, et al. ∙

∙ 05/22/2022

Addressing Strategic Manipulation Disparities in Fair Classification

In real-world classification settings, individuals respond to classifier...

0 Vijay Keswani, et al. ∙

∙ 07/15/2021

Auditing for Diversity using Representative Examples

Assessing the diversity of a dataset of information associated with peop...

0 Vijay Keswani, et al. ∙

∙ 06/10/2021

Fair Classification with Adversarial Perturbations

We study fair classification in the presence of an omniscient adversary ...

0 L. Elisa Celis, et al. ∙

∙ 11/09/2020

Mitigating Bias in Set Selection with Noisy Protected Attributes

Subset selection algorithms are ubiquitous in AI-driven applications, in...

0 Anay Mehrotra, et al. ∙

∙ 10/21/2020

The Effect of the Rooney Rule on Implicit Bias in the Long Term

A robust body of evidence demonstrates the adverse effects of implicit b...

0 L. Elisa Celis, et al. ∙

∙ 07/15/2020

Dialect Diversity in Text Summarization on Twitter

Extractive summarization algorithms can be used on Twitter data to retur...

0 L. Elisa Celis, et al. ∙

∙ 06/08/2020

Fair Classification with Noisy Protected Attributes

Due to the growing deployment of classification algorithms in various so...

0 L. Elisa Celis, et al. ∙

∙ 01/23/2020

Interventions for Ranking in the Presence of Implicit Bias

Implicit bias is the unconscious attribution of particular qualities (or...

0 L. Elisa Celis, et al. ∙

∙ 11/04/2019

Assessing Social and Intersectional Biases in Contextualized Word Representations

Social bias in machine learning has drawn significant attention, with wo...

0 Yi Chern Tan, et al. ∙

∙ 06/05/2019

Fair Distributions from Biased Samples: A Maximum Entropy Optimization Framework

One reason for the emergence of bias in AI systems is biased data -- dat...

0 L. Elisa Celis, et al. ∙

∙ 01/29/2019

Toward Controlling Discrimination in Online Ad Auctions

Online advertising platforms are thriving due to the customizable audien...

0 L. Elisa Celis, et al. ∙

∙ 01/29/2019

Fair Online Advertising

Online advertising platforms are thriving due to the customizable audien...

0 L. Elisa Celis, et al. ∙

∙ 01/29/2019

Improved Adversarial Learning for Fair Classification

Motivated by concerns that machine learning algorithms may introduce sig...

0 L. Elisa Celis, et al. ∙

∙ 01/29/2019

Implicit Diversity in Image Summarization

Case studies, such as Kay et al., 2015 have shown that in image summariz...

0 L. Elisa Celis, et al. ∙

∙ 06/24/2018

Balanced News Using Constrained Bandit-based Personalization

We present a prototype for a news search engine that presents balanced v...

0 Sayash Kapoor, et al. ∙

∙ 06/15/2018

Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees

Developing classification algorithms that are fair with respect to sensi...

0 L. Elisa Celis, et al. ∙

∙ 02/23/2018

An Algorithmic Framework to Control Bias in Bandit-based Personalization

Personalization is pervasive in the online space as it leads to higher e...

0 L. Elisa Celis, et al. ∙

∙ 02/12/2018

Fair and Diverse DPP-based Data Summarization

Sampling methods that choose a subset of the data proportional to its di...

0 L. Elisa Celis, et al. ∙

∙ 12/08/2017

Stochastic Dual Coordinate Descent with Bandit Sampling

Coordinate descent methods minimize a cost function by updating a single...

0 Farnood Salehi, et al. ∙

∙ 10/27/2017

Group Fairness in Multiwinner Voting

We study multiwinner voting problems when there is an additional require...

0 L. Elisa Celis, et al. ∙

∙ 08/08/2017

Stochastic Optimization with Bandit Sampling

Many stochastic optimization algorithms work by estimating the gradient ...

0 Farnood Salehi, et al. ∙

∙ 08/01/2016

On the Complexity of Constrained Determinantal Point Processes

Determinantal Point Processes (DPPs) are probabilistic models that arise...

0 L. Elisa Celis, et al. ∙

∙ 03/14/2016

Sequential Voting Promotes Collective Discovery in Social Recommendation Systems

One goal of online social recommendation systems is to harness the wisdo...

0 L. Elisa Celis, et al. ∙

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