Predicting Data Scientist Stuckness During the Development of Machine Learning Classifiers
Moshe Mash, Shoshana Oryol, Stephanie Rosenthal, and Reid Simmons.
Will be presented at VL/HCC (the IEEE Symposium on Visual Languages and Human-Centric Computing) 2022. Link
Tracking Data Transformations to Support Data Science Workflows
Moshe Mash, Stephanie Rosenthal, and Reid Simmons.
DSWorkFlow: A Framework for Capturing Data Scientists’ Workflows
CHI Conference on Human Factors in Computing Systems 2021. [CHI paper]
How to Form Winning Coalitions in Mixed Human-Computer Settings
Moshe Mash, Yair Zick, Yoram Bachrach, and Kobi Gal.
The 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017. [IJCAI paper]
Which Is the Fairest (Rent Division) of Them All?
Ya'akov (Kobi) Gal, Moshe Mash, Ariel D. Procaccia and Yair Zick. The 17th ACM Conference on Economics and Computation (EC), 2016.
Best paper award.
Peer-designed agents for reliably evaluating the distribution of outcomes in
environments involving people.
Moshe Mash, Raz Lin and David Sarne. The 13th ACM conference on Autonomous agents and multi-agent systems (AAMAS), 2014.
Join me with the weakest partner please.
Moshe Mash, Igor Rochlin and David Sarne. The 12th IEEE/WIC/ACM conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012.
Human-Computer Coalition Formation in Weighted Voting Games.
Moshe Mash, Roy Fairstein, Yair Zick, Yoram Bachrach and Kobi Gal.
ACM Transactions on Intelligent Systems and Technology (TIST), 2020.
[ACM TIST paper]
Ya'akov (Kobi) Gal, Moshe Mash, Ariel D. Procaccia and Yair Zick. Journal of the ACM (JACM), 2017.
Joint search with self-interested agents and the failure of cooperation enhancers
Igor Rochlin, David Sarne and Moshe Mash.
Artificial Intelligence Journal (AIJ), 2014.