Accepted Papers

Designing Long-term Group Fair Policies in Dynamical Systems

Miriam Rateike · Isabel Valera · Patrick Forré

Learning in reverse causal strategic environments with ramifications on two sided markets

Seamus Somerstep · Yuekai Sun · Ya'acov Ritov

Repairing Regressors for Fair Binary Classification at Any Decision Threshold

Kweku Kwegyir-Aggrey · Jessica Dai · A. Feder Cooper · John Dickerson · Suresh Venkatasubramanian · Keegan Hines

Backtracking Counterfactual Fairness

Lucius Bynum · Joshua Loftus · Julia Stoyanovich

Information-Theoretic Bounds on The Removal of Attribute-Specific Bias From Neural Networks 

Jiazhi Li · Mahyar Khayatkhoei · Jiageng Zhu · Hanchen Xie · Mohamed Hussein · Wael Abd-Almageed

Is My Prediction Arbitrary? Confounding Effects of Variance in Fair Classification 

A. Feder Cooper · Katherine Lee · Madiha Choksi · Solon Barocas · Christopher De Sa · James Grimmelmann · Jon Kleinberg · Siddhartha Sen · Baobao Zhang

Procedural Fairness Through Decoupling Objectionable Data Generating Components 

Zeyu Tang · Jialu Wang · Yang Liu · Peter Spirtes · Kun Zhang

Exploring Predictive Arbitrariness as Unfairness via Predictive Multiplicity and Predictive Churn 

Jamelle Watson-Daniels · Lance Strait · Mehadi Hassen · Amy Skerry-Ryan · Alexander D'Amour

Improving Fairness-Accuracy tradeoff with few Test Samples under Covariate Shift

Shreyas Havaldar · Jatin Chauhan · Karthikeyan Shanmugam · Jay Nandy · Aravindan Raghuveer

Loss Modeling for Multi-Annotator Datasets 

Uthman Jinadu · Jesse Annan · Shanshan Wen · Yi Ding

Measuring fairness of synthetic oversampling on credit datasets 

Decio Miranda Filho · Thalita Veronese · Marcos M. Raimundo

Transparency Through the Lens of Recourse and Manipulation

Yatong Chen · Andrew Estornell · Yevgeniy Vorobeychik · Yang Liu

Variation of Gender Biases in Visual Recognition Models Before and After Finetuning 

Jaspreet Ranjit · Tianlu Wang · Baishakhi Ray · Vicente Ordonez

On Comparing Fair classifiers under Data Bias 

mohit sharma · Amit Deshpande · Rajiv Ratn Shah

Reevaluating COMPAS: Base Rate Tracking and Racial Bias 

Victor Crespo · Javier Rando · Benjamin Eva · Vijay Keswani · Walter Sinnott-Armstrong

Performativity and Prospective Fairness. 

Sebastian Zezulka · Konstantin Genin

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Explaining knock-on effects of bias mitigation

Svetoslav Nizhnichenkov · Rahul Nair · Elizabeth Daly · Brian Mac Namee

On Mitigating Unconscious Bias through Bandits with Evolving Biased Feedback 

Matthew Faw · Constantine Caramanis · Sanjay Shakkottai · Jessica Hoffmann

Everything, Everywhere All in One Evaluation: Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness

Jan Simson · Florian Pfisterer · Christoph Kern

Fairer and More Accurate Models Through NAS

Richeek Das · Samuel Dooley

Fairness in link analysis ranking algorithms

Ana-Andreea Stoica · Augustin Chaintreau · Nelly Litvak

A Causal Perspective on Label Bias

Vishwali Mhasawade · Alexander D'Amour · Stephen Pfohl

Remembering to Be Fair: On Non-Markovian Fairness in Sequential Decision Making 

Parand A. Alamdari · Toryn Klassen · Elliot Creager · Sheila McIlraith

FAIR-Ensemble: Homogeneous Deep Ensembling Naturally Attenuates Disparate Group Performances

Wei-Yin Ko · Daniel Dsouza · Karina Nguyen · Randall Balestriero · Sara Hooker

Fair Clustering: Critique and Future Directions 

John Dickerson · Seyed Esmaeili · Jamie Morgenstern · Claire Jie Zhang

Seller-side Outcome Fairness in Online Marketplaces

Zikun Ye · Reza Yousefi Maragheh · Lalitesh Morishetti · Shanu Vashishtha · Jason Cho · Kaushiki Nag · Sushant Kumar · Kannan Achan

Mitigating stereotypical biases in text to image generative systems

Piero Esposito · Parmida Atighehchian · Anastasis Germanidis · Deepti Ghadiyaram

Dr. FERMI: A Stochastic Distributionally Robust Fair Empirical Risk Minimization Framework 

Sina Baharlouei · Meisam Razaviyayn

Causal Dependence Plots

Joshua Loftus · Lucius Bynum · Sakina Hansen

It’s About Time: Fairness and Temporal Depth 

Joshua Loftus

On The Vulnerability of Fairness Constrained Learning to Malicious Noise 

Avrim Blum · Princewill Okoroafor · Aadirupa Saha · Kevin Stangl

Model Fairness is Constrained by Decision Making Strategy Design 

Alexandra Stolyarova

Algorithmic Fairness Reproducibility: A Close Look at Data Usage over the Years 

Jan Simson · Alessandro Fabris · Christoph Kern

Bayesian Multilevel Regression and Poststratification for Dynamic Diversity-Aware Modeling 

Nicole Osayande · Danilo Bzdok

The Long-Term Effects of Personalization: Evidence from Youtube 

Andreas Haupt · Mihaela Curmei · François-Marie de Jouvencel · Marc Faddoul · Benjamin Recht · Dylan Hadfield-Menell

Allocating Bonus Points in Sequential Matchings with Preference Dynamics 

Meirav Segal · Liu Leqi · Anne-Marie George · Christos Dimitrakakis · Hoda Heidari

Equal Opportunity under Performative Effects 

Sophia Gunluk · Dhanya Sridhar · Antonio Gois · Simon Lacoste-Julien

Assessing Perceived Fairness in Machine Learning (ML) Process: A Conceptual Framework 

Anoop Mishra · Deepak Khazanchi

Unbiased Sequential Prediction for Fairness in Predictions-to-Decisions Pipelines 

Georgy Noarov · Ramya Ramalingam · Aaron Roth · Stephan Xie

Deep Reinforcement Learning for Efficient and Fair Allocation of Healthcare Resources

Yikuan Li

What Comes After Auditing: Distinguishing Between Algorithmic Errors and Task Specification Issues 

Charvi Rastogi

On Hedden's Proof that Machine Learning Fairness Metrics are Flawed 

Anders Søgaard · Klemens Kappel · Thor Grünbaum

Achieving Counterfactual Fairness in Changing Environments via Sequential Autoencoder 

Yujie Lin · Chen Zhao · Minglai Shao · Xujiang Zhao · Baoluo Meng · Haifeng Chen

Are computational interventions to advance fair lending robust to different modeling choices about the nature of lending? 

Benjamin Laufer · Manish Raghavan · Solon Barocas

Improving Fairness in Facial Recognition Models with Distribution Shifts 

Gianluca Barone · Aashrit Cunchala · Rudy Nunez · Nicole Yang

Beyond Expectations: Model-Driven Amplification of Dataset Biases in Data Feedback Loops 

Rylan Schaeffer · Oluwasanmi Koyej

Detecting Electricity Service Equity Issues with Transfer Counterfactual Learning on Large-Scale Outage Datasets  

Song Wei · Xiangrui Kong · Sarah Huestis-Mitchell · Yao Xie · Shixiang Zhu · Alinson Xavier · Feng Qiu

Democratise with Care: The need for fairness specific features in user-interface based open source AutoML tools 

Sundaraparipurnan Narayanan