85 citations · 196 across the 12 of their papers we have counts for
4 papers · 1 filter
Empirical Risk Minimization under Fairness Constraints
Michele Donini, Luca Oneto, Shai Ben-David +2
We address the problem of algorithmic fairness: ensuring that sensitive variables do not unfairly influence the outcome of a classifier. We present an approach based on empirical r…
Multi-task and Lifelong Learning of Kernels
Anastasia Pentina, Shai Ben-David
We consider a problem of learning kernels for use in SVM classification in the multi-task and lifelong scenarios and provide generalization bounds on the error of a large margin cl…
Clustering is Easy When ....What?
Shai Ben-David
It is well known that most of the common clustering objectives are NP-hard to optimize. In practice, however, clustering is being routinely carried out. One approach for providing…
Representation Learning for Clustering: A Statistical Framework
Hassan Ashtiani, Shai Ben-David
We address the problem of communicating domain knowledge from a user to the designer of a clustering algorithm. We propose a protocol in which the user provides a clustering of a r…