Milan Mossé

According to our database, Milan Mossé authored at least 12 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Stable Voting and the Splitting of Cycles.

Wesley H. Holliday, Milan Mossé, Chase Norman, Eric Pacuit, Cynthia Wang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Modeling Discrimination with Causal Abstraction.

Milan Mossé, Kara Schechtman, Frederick Eberhardt, Thomas Icard

CoRR, January, 2025

2024

Is Causal Reasoning Harder than Probabilistic Reasoning?

Milan Mossé, Duligur Ibeling, Thomas Icard

Rev. Symb. Log., 2024

On Probabilistic and Causal Reasoning with Summation Operators.

Duligur Ibeling, Thomas F. Icard III, Milan Mossé

CoRR, 2024

Social Choice for AI Alignment: Dealing with Diverse Human Feedback.

Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Mossé, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, William S. Zwicker

CoRR, 2024

Probing the quantitative-qualitative divide in probabilistic reasoning.

Duligur Ibeling, Thomas Icard, Krzysztof Mierzewski, Milan Mossé

Ann. Pure Appl. Log., 2024

Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback.

Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Mossé, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, William S. Zwicker

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Multiplicative Metric Fairness Under Composition.

Milan Mossé

Proceedings of the 4th Symposium on Foundations of Responsible Computing, 2023

2022

A Generalization of the Satisfiability Coding Lemma and Its Applications.

Milan Mossé, Harry Sha, Li-Yang Tan

Proceedings of the 25th International Conference on Theory and Applications of Satisfiability Testing, 2022

2021

Conditional Negative Sampling for Contrastive Learning of Visual Representations.

Mike Wu, Milan Mossé, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

On Mutual Information in Contrastive Learning for Visual Representations.

Mike Wu, Chengxu Zhuang, Milan Mossé, Daniel Yamins, Noah D. Goodman

CoRR, 2020

2019

Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference.

Mike Wu, Milan Mossé, Noah D. Goodman, Chris Piech

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019