Accepted Papers

Please refer to the poster ID and category to navigate during the poster session

Oral Presentations

  • P7: The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective Poster | Arxiv

Naman Goel (ETH Zurich), Alfonso Amayuelas (EPFL Lausanne), Amit Deshpande (Microsoft Research), Amit Sharma (Microsoft Research)

  • P34: Fairness in Risk Assessment: Post-Processing to Achieve Counterfactual Equalized Odds Poster | Arxiv

Alan Mishler (CMU)*; Edward H Kennedy (Carnegie Mellon University); Alexandra Chouldechova (CMU)

  • P43: Inherent Trade-Offs in the Fair Allocation of Treatment Poster | Arxiv

Yuzi He (University of Southern California)*; Keith Burghardt (ISI, University of Southern California ); Kristina Lerman (ISI, University of Southern California)

  • P8: Foundations for Languages for Interpretability and Bias Detection Poster | Arxiv

Bernardo Subercaseaux (Universidad de Chile)*; Jorge Pérez (Department of Computer Science, Universidad de Chile); Pablo Barceló (PUC Chile & Millenium Instititute for Foundational Research on Data)

  • P30: Fairness and Robustness in Invariant Learning: A Case Study in Toxicity Classification Poster | Arxiv

Robert Adragna (University of Toronto)*; Elliot Creager (University of Toronto); David Madras (University of Toronto); Richard Zemel (University of Toronto)

  • P41: Group Fairness by Probabilistic Modeling with Latent Fair Decisions Poster | Arxiv

YooJung Choi (UCLA)*; Meihua Dang (UCLA); Guy Van den Broeck (UCLA)


  • P12: Shortcomings of Counterfactual Fairness and a Proposed Modification Poster | Arxiv

Fabian Beigang (London School of Economics)

  • P13: On the Fairness of Causal Algorithmic Recourse Poster | Arxiv

Julius von Kügelgen (MPI for Intelligent Systems, Tübingen & University of Cambridge)*; Umang Bhatt (University of Cambridge); Amir-Hossein Karimi (MPI for Intelligent Systems, Tübingen); Isabel Valera (MPI for Intelligent Systems); Adrian Weller (University of Cambridge); Bernhard Schölkopf (MPI for Intelligent Systems, Tübingen)

  • P24: Exchanging Lessons Between Algorithmic Fairness and Domain Generalization Poster | Arxiv

Elliot Creager (University of Toronto)*; Joern-Henrik Jacobsen (Vector Institute); Richard Zemel (University of Toronto)

  • P33: Algorithmic Approaches to Equal Opportunity and Affirmative Action via Counterfactual Predictions Poster | Arxiv

Yixin Wang (Columbia University)*; Dhanya Sridhar (Columbia University); David Blei (Columbia University)

  • P16: A critique of the use of counterfactuals in fair machine learning Poster | Arxiv

Atoosa Kasirzadeh (University of Toronto and Australian National University)*; Andrew Smart (Google Inc.)


  • P18: Towards Auditability for Fairness in Deep Learning Poster | Arxiv

Ivoline C. Ngong (Konya Technical University); Krystal Maughan (University of Vermont); Joseph Near (University of Vermont)*

  • P26: Augmented Fairness: An Interpretable Model Augmenting Decision-Makers' Fairness Poster | Arxiv

Tong Wang (University of Iowa)*; Maytal Saar-Tsechansky ()

  • P31: Debiasing Convolutional Neural Networks via Meta Orthogonalization Poster | Arxiv

Kurtis Evan A David (UT Austin)*; Ruth C Fong (University of Oxford); Qiang Liu (UT Austin)

Fairness metrics/mitigation

  • P11: The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets Poster | Arxiv

Vid Kocijan (University of Oxford)*; Oana-Maria Camburu (University of Oxford); Thomas Lukasiewicz (University of Oxford)

  • P21: Selective Classification Can Magnify Disparities Across Groups Poster | Arxiv

Erik Jones (Stanford University )*; Shiori Sagawa (Stanford University); Pang Wei Koh (Stanford University); Ananya Kumar (Stanford University); Percy Liang (Stanford University)

Ashkan Rezaei (University of Illinois at Chicago)*; Anqi Liu (California Institute of Technology); Omid Memarrast (University of Illinois at Chicago); Brian Ziebart (UIC)

  • P27: An example of prediction which complies with Demographic Parity and equalizes group-wise risks in the context of regression Poster | Arxiv

Nicolas Schreuder (CREST)*; Evgenii Chzhen (Université Paris-Saclay)

  • P29: On Statistical Discrimination as a Failure of Social Learning: A Multi-Armed Bandit Approach Poster | Arxiv

Junpei Komiyama (New York University)*; Shunya Noda (University of British Columbia, Vancouver School of Economics)