Papers

Conference Papers

• On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks (open review)
  Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T Schaub, and Danai Koutra
  LoG 2023
  
  
• It’s Not Fairness, and It’s Not Fair: The Failure of Distributional Equality and the Promise of Relational Equality in Complete-Information Hiring Games (arXiv)
  Benjamin Fish and Luke Stark
  EAAMO 2022
  
  
• Reflexive Design of Fairness and Other Human Values in Formal Models (arXiv)
  Benjamin Fish and Luke Stark
  AIES 2021
  
  
• The Effect of Competition and Regulation on Error Inequality in Data-Driven Markets (pdf)
  Hadi Elzayn and Benjamin Fish
  FAT* (FAccT) 2020
  
  
• Sampling without compromising accuracy in adaptive data analysis (pdf)
  Benjamin Fish, Lev Reyzin, and Benjamin I.P. Rubinstein
  ALT 2020
  
  
• Gaps in Information Access in Social Networks (pdf)
  Benjamin Fish, Ashkan Bashardoust, danah boyd, Sorelle A. Friedler, Carlos Scheidegger, and Suresh Venkatasubramanian
  WWW 2019
  
  
• On the Complexity of Learning from Label Proportions (corrected and extended by JAIR 2020 pdf)
  Benjamin Fish and Lev Reyzin
  IJCAI 2017
  
  
• Recovering Social Networks by Observing Votes (pdf)
  Benjamin Fish, Yi Huang, and Lev Reyzin
  AAMAS 2016, ISAIM 2016
  
  
• A Confidence-Based Approach for Balancing Fairness and Accuracy (pdf)
  Benjamin Fish, Jeremy Kun, and Adam D. Lelkes
  SDM 2016
  
  
• Handling oversampling in dynamic networks using link prediction (pdf)
  Benjamin Fish and Rajmonda S. Caceres
  ECML 2015
  
  
• On the Computational Complexity of MapReduce (pdf, slides)
  Benjamin Fish, Jeremy Kun, Adam D. Lelkes, Lev Reyzin, and Gyorgy Turan
  DISC 2015
  
  
• CSPs and Connectedness: P/NP Dichotomy for Idempotent, Right Quasigroups (pdf)
  Benjamin Fish, Robert W. McGrail, James Belk, Solomon Garber, and Japheth Wood
  SYNASC 2014
  
  
• Feature selection based on mutual information for human activity recognition (link)
  Benjamin Fish, Ammar Khan, Nabil Hajj Chehade, Chieh Chien, and Greg Pottie
  ICASSP 2012
  

Journal Papers

• Responsible Computing During COVID-19 and Beyond (link)
  Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daume III, Miroslav Dudik, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, and Marion Zepf
  CACM 2021
  
  
• On the Complexity of Learning a Class Ratio from Unlabeled Data (pdf)
  Benjamin Fish and Lev Reyzin
  Journal of Artifical Intelligence Research 2020
  
  
• Betweenness centrality profiles in trees (link, arXiv)
  Benjamin Fish, Rahul Kushwaha, and Gyorgy Turan
  Journal of Complex Networks 2017
  
  
• Zero-sum flows of the linear lattice (link)
  With Ghassan Sarkis, Shahriar Shahriari, and the Pomona College Undergraduate Research Circle
  Finite Fields and their Application 2015
  
  
• Diamond-free subsets in the linear lattices (link)
  With Ghassan Sarkis, Shahriar Shahriari, and the Pomona College Undergraduate Research Circle
  Order 2013
  
  

Workshop/Short Papers

• Beliefs, Relationships, and Equality: An Alternative Source of Discrimination in a Symmetric Hiring Market via Threats (arXiv)
  Benjamin Fish and Luke Stark
  BIAS 2023 (ECML 2023)
  
  
• On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods (arXiv)
  Benjamin Fish and Luke Stark
  DLG 2022 (KDD 2022)
  
  
• Responsible Computing During COVID-19 and Beyond (link)
  Solon Barocas, Asia J Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miroslav Dudík, Benjamin Fish, Mary L Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, and Marion Zepf
  Communications of the ACM 2021
  
  
• Sublinear-Time Adaptive Data Analysis (superceded by ALT 2020, see pdf)
  Benjamin Fish, Lev Reyzin, and Benjamin I. P. Rubinstein
  ISAIM 2018
  
  
• A task-driven approach to time scale detection in dynamic networks (pdf)
  Benjamin Fish and Rajmonda S. Caceres
  MLG 2017 (KDD 2017)
  
  
• Open Problem: Meeting Times for Learning Random Automata (pdf)
  Benjamin Fish and Lev Reyzin
  COLT 2017
  
  
• Fair Boosting: A Case Study (pdf)
  Benjamin Fish, Jeremy Kun, and Adam D. Lelkes
  FAT-ML 2015 (ICML 2015)
  
  

Theses

• New Models and Algorithms for Data Analysis (pdf)
  Advised by Lev Reyzin
  PhD. Thesis, 2018
  
  
• The Word Problem in Quandles (pdf)
  Advised by Rena Levitt
  B.A. Thesis, 2013
  
  
• The Cophylogeny Reconstruction Problem (pdf)
  Advised by Ran Libeskind-Hadas
  B.A. Thesis, 2013