Feature selection based on mutual information for human activity recognition. - Benjamin Fish; Ammar Khan; Mohamed Nabil Hajj Chehade; Chieh Chien; Gregory J. Pottie (ICASSP, 2012)

CSPs and Connectedness: P/NP Dichotomy for Idempotent, Right Quasigroups. - Robert W. McGrail; James M. Belk; Solomon Garber; Japheth Wood; Benjamin Fish (SYNASC, 2014)

Handling Oversampling in Dynamic Networks Using Link Prediction. - Benjamin Fish; Rajmonda Sulo Caceres (ECML/PKDD (2), 2015)

On the Computational Complexity of MapReduce. - Benjamin Fish; Jeremy Kun; Ádám Dániel Lelkes; Lev Reyzin; György Turán (DISC, 2015)

Recovering Social Networks by Observing Votes. - Benjamin Fish; Yi Huang; Lev Reyzin (ISAIM, 2016)

A Confidence-Based Approach for Balancing Fairness and Accuracy. - Benjamin Fish; Jeremy Kun; Ádám Dániel Lelkes (SDM, 2016)

Open Problem: Meeting Times for Learning Random Automata. - Benjamin Fish; Lev Reyzin (COLT, 2017)

On the Complexity of Learning from Label Proportions. - Benjamin Fish; Lev Reyzin (IJCAI, 2017)

Betweenness centrality profiles in trees. - Benjamin Fish; Rahul Kushwaha; György Turán (J. Complex Networks, 2017)

A supervised approach to time scale detection in dynamic networks. - Benjamin Fish; Rajmonda Sulo Caceres (CoRR, 2017)

Sublinear-Time Adaptive Data Analysis. - Benjamin Fish; Lev Reyzin; Benjamin I. P. Rubinstein (ISAIM, 2018)

Gaps in Information Access in Social Networks? - Benjamin Fish; Ashkan Bashardoust; danah boyd; Sorelle A. Friedler; Carlos Scheidegger; Suresh Venkatasubramanian (WWW, 2019)

Sampling Without Compromising Accuracy in Adaptive Data Analysis. - Benjamin Fish; Lev Reyzin; Benjamin I. P. Rubinstein (ALT, 2020)

When not to design, build, or deploy. - Solon Barocas; Asia J. Biega; Benjamin Fish; Jedrzej Niklas; Luke Stark (FAT*, 2020)

The effects of competition and regulation on error inequality in data-driven markets. - Hadi Elzayn; Benjamin Fish (FAT*, 2020)

On the Complexity of Learning a Class Ratio from Unlabeled Data. - Benjamin Fish; Lev Reyzin (J. Artif. Intell. Res., 2020)

Reflexive Design for Fairness and Other Human Values in Formal Models. - Benjamin Fish; Luke Stark (AIES, 2021)

Responsible computing during COVID-19 and beyond. - Solon Barocas; Asia J. Biega; Margarita Boyarskaya; Kate Crawford 002; Hal Daumé III; Miroslav Dudík; Benjamin Fish; Mary L. Gray; Brent J. Hecht; Alexandra Olteanu; Forough Poursabzi-Sangdeh; Luke Stark; et al. (Commun. ACM, 2021)

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. - Benjamin Fish; Luke Stark (EAAMO, 2022)

On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods. - Donald Loveland; Jiong Zhu; Mark Heimann; Benjamin Fish; Michael T. Schaub; Danai Koutra (CoRR, 2022)

On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks. - Donald Loveland; Jiong Zhu; Mark Heimann; Benjamin Fish; Michael T. Schaub; Danai Koutra (LoG, 2023)

Beliefs, Relationships, and Equality: An Alternative Source of Discrimination in a Symmetric Hiring Market via Threats. - Serafina Kamp; Therese Nkeng; Vicente Riquelme; Benjamin Fish (PKDD/ECML Workshops (1), 2023)

Equal Merit Does Not Imply Equality: Discrimination at Equilibrium in a Hiring Market with Symmetric Agents. - Serafina Kamp; Benjamin Fish (AAAI, 2025)

Centralization vs Decentralization in Hiring and Admissions. - Benjamin Fish; Diptangshu Sen; Juba Ziani (CoRR, 2025)

Last-Iterate Convergence of No-Regret Learning for Equilibria in Bargaining Games. - Serafina Kamp; Reese Liebman; Benjamin Fish (CoRR, 2025)