Krishna P. Gummadi

research

∙ 05/31/2023

Diffused Redundancy in Pre-trained Representations

Representations learned by pre-training a neural network on a large data...

0 Vedant Nanda, et al. ∙

research

∙ 05/30/2023

Pointwise Representational Similarity

With the increasing reliance on deep neural networks, it is important to...

0 Camila Kolling, et al. ∙

research

∙ 05/28/2023

Understanding Blockchain Governance: Analyzing Decentralized Voting to Amend DeFi Smart Contracts

Smart contracts are contractual agreements between participants of a blo...

0 Johnnatan Messias, et al. ∙

research

∙ 02/14/2023

Dissecting Bitcoin and Ethereum Transactions: On the Lack of Transaction Contention and Prioritization Transparency in Blockchains

In permissionless blockchains, transaction issuers include a fee to ince...

0 Johnnatan Messias, et al. ∙

research

∙ 01/12/2023

Leveraging Rights of Data Subjects for Social Media Analysis: Studying TikTok via Data Donations

TikTok is a relatively novel and widely popular media platform. In respo...

0 Savvas Zannettou, et al. ∙

research

∙ 09/08/2022

Taking Advice from (Dis)Similar Machines: The Impact of Human-Machine Similarity on Machine-Assisted Decision-Making

Machine learning algorithms are increasingly used to assist human decisi...

0 Nina Grgić-Hlača, et al. ∙

research

∙ 06/23/2022

Measuring Representational Robustness of Neural Networks Through Shared Invariances

A major challenge in studying robustness in deep learning is defining th...

33 Vedant Nanda, et al. ∙

research

∙ 05/10/2022

Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making

Decision making algorithms, in practice, are often trained on data that ...

31 Miriam Rateike, et al. ∙

research

∙ 04/26/2022

Scheduling Virtual Conferences Fairly: Achieving Equitable Participant and Speaker Satisfaction

Recently, almost all conferences have moved to virtual mode due to the p...

13 Gourab K Patro, et al. ∙

research

∙ 04/01/2022

FaiRIR: Mitigating Exposure Bias from Related Item Recommendations in Two-Sided Platforms

Related Item Recommendations (RIRs) are ubiquitous in most online platfo...

0 Abhisek Dash, et al. ∙

research

∙ 02/08/2022

Alexa, in you, I trust! Fairness and Interpretability Issues in E-commerce Search through Smart Speakers

In traditional (desktop) e-commerce search, a customer issues a specific...

0 Abhisek Dash, et al. ∙

research

∙ 01/19/2022

"Learn the Facts About COVID-19": Analyzing the Use of Warning Labels on TikTok Videos

During the COVID-19 pandemic, health-related misinformation and harmful ...

0 Chen Ling, et al. ∙

research

∙ 12/26/2021

Towards Fair Recommendation in Two-Sided Platforms

Many online platforms today (such as Amazon, Netflix, Spotify, LinkedIn,...

0 Arpita Biswas, et al. ∙

research

∙ 12/10/2021

On Fair Selection in the Presence of Implicit and Differential Variance

Discrimination in selection problems such as hiring or college admission...

0 Vitalii Emelianov, et al. ∙

research

∙ 11/29/2021

Exploring Alignment of Representations with Human Perception

We argue that a valuable perspective on when a model learns good represe...

4 Vedant Nanda, et al. ∙

research

∙ 10/22/2021

Selfish Opaque Transaction Ordering in the Bitcoin Blockchain: The Case for Chain Neutrality

Most public blockchain protocols, including the popular Bitcoin and Ethe...

0 Johnnatan Messias, et al. ∙

research

∙ 09/09/2021

Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning

Reliably predicting potential failure risks of machine learning (ML) sys...

45 Preethi Lahoti, et al. ∙

research

∙ 06/05/2021

Modeling Coordinated vs. P2P Mining: An Analysis of Inefficiency and Inequality in Proof-of-Work Blockchains

We study efficiency in a proof-of-work blockchain with non-zero latencie...

0 Mohamed Alzayat, et al. ∙

research

∙ 05/10/2021

Loss-Aversively Fair Classification

The use of algorithmic (learning-based) decision making in scenarios tha...

0 Junaid Ali, et al. ∙

research

∙ 05/10/2021

Accounting for Model Uncertainty in Algorithmic Discrimination

Traditional approaches to ensure group fairness in algorithmic decision ...

0 Junaid Ali, et al. ∙

research

∙ 05/06/2021

CrossWalk: Fairness-enhanced Node Representation Learning

The potential for machine learning systems to amplify social inequities ...

0 Ahmad Khajehnejad, et al. ∙

research

∙ 01/30/2021

When the Umpire is also a Player: Bias in Private Label Product Recommendations on E-commerce Marketplaces

Algorithmic recommendations mediate interactions between millions of cus...

0 Abhisek Dash, et al. ∙

research

∙ 10/24/2020

On Fair Virtual Conference Scheduling: Achieving Equitable Participant and Speaker Satisfaction

The (COVID-19) pandemic-induced restrictions on travel and social gather...

12 Gourab K Patro, et al. ∙

research

∙ 07/01/2020

Unifying Model Explainability and Robustness via Machine-Checkable Concepts

As deep neural networks (DNNs) get adopted in an ever-increasing number ...

8 Vedant Nanda, et al. ∙

research

∙ 06/24/2020

On Fair Selection in the Presence of Implicit Variance

Quota-based fairness mechanisms like the so-called Rooney rule or four-f...

0 Vitalii Emelianov, et al. ∙

research

∙ 05/19/2020

Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy

Fairness concerns about algorithmic decision-making systems have been ma...

0 Bashir Rastegarpanah, et al. ∙

research

∙ 02/25/2020

FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms

We investigate the problem of fair recommendation in the context of two-...

16 Gourab K Patro, et al. ∙

research

∙ 10/30/2019

DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning

We introduce a framework for dynamic adversarial discovery of informatio...

26 Michiel A. Bakker, et al. ∙

research

∙ 10/22/2019

An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision

The notion of individual fairness requires that similar people receive s...

16 Hanchen Wang, et al. ∙

research

∙ 09/22/2019

Incremental Fairness in Two-Sided Market Platforms: On Smoothly Updating Recommendations

Major online platforms today can be thought of as two-sided markets with...

0 Gourab K Patro, et al. ∙

research

∙ 09/22/2019

Incremental Fairness in Two-Sided Market Platforms: On Updating Recommendations Fairly

Major online platforms today can be thought of as two-sided markets with...

0 Gourab K Patro, et al. ∙

research

∙ 09/12/2019

Minimizing Margin of Victory for Fair Political and Educational Districting

In many practical scenarios, a population is divided into disjoint group...

0 Ana-Andreea Stoica, et al. ∙

research

∙ 07/02/2019

Operationalizing Individual Fairness with Pairwise Fair Representations

We revisit the notion of individual fairness proposed by Dwork et al. A ...

1 Preethi Lahoti, et al. ∙

research

∙ 05/16/2019

On the Fairness of Time-Critical Influence Maximization in Social Networks

Influence maximization has found applications in a wide range of real-wo...

0 Junaid Ali, et al. ∙

research

∙ 03/04/2019

On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning

Most existing notions of algorithmic fairness are one-shot: they ensure ...

0 Hoda Heidari, et al. ∙

research

∙ 12/02/2018

Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems

The increasing role of recommender systems in many aspects of society ma...

0 Bashir Rastegarpanah, et al. ∙

research

∙ 09/10/2018

A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity

Equality of opportunity (EOP) is an extensively studied conception of fa...

4 Hoda Heidari, et al. ∙

research

∙ 07/02/2018

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices

Discrimination via algorithmic decision making has received considerable...

0 Till Speicher, et al. ∙

research

∙ 06/13/2018

Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making

We draw attention to an important, yet largely overlooked aspect of eval...

0 Hoda Heidari, et al. ∙

research

∙ 06/08/2018

Blind Justice: Fairness with Encrypted Sensitive Attributes

Recent work has explored how to train machine learning models which do n...

0 Niki Kilbertus, et al. ∙

research

∙ 06/04/2018

iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making

People are rated and ranked, towards algorithmic decision making in an i...

0 Preethi Lahoti, et al. ∙

research

∙ 05/04/2018

Equity of Attention: Amortizing Individual Fairness in Rankings

Rankings of people and items are at the heart of selection-making, match...

0 Asia J. Biega, et al. ∙

research

∙ 02/26/2018

Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction

As algorithms are increasingly used to make important decisions that aff...

0 Nina Grgić-Hlača, et al. ∙

research

∙ 06/30/2017

From Parity to Preference-based Notions of Fairness in Classification

The adoption of automated, data-driven decision making in an ever expand...

0 Muhammad Bilal Zafar, et al. ∙

research

∙ 06/30/2017

On Fairness, Diversity and Randomness in Algorithmic Decision Making

Consider a binary decision making process where a single machine learnin...

0 Nina Grgić-Hlača, et al. ∙

research

∙ 10/31/2016

The Case for Temporal Transparency: Detecting Policy Change Events in Black-Box Decision Making Systems

Bringing transparency to black-box decision making systems (DMS) has bee...

0 Miguel Ferreira, et al. ∙

research

∙ 10/26/2016

Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

Automated data-driven decision making systems are increasingly being use...

0 Muhammad Bilal Zafar, et al. ∙

Krishna P. Gummadi

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