collaborators

5 papers

cs.LG2026

How Deep Are Deep GPs, Really? A Sharp Threshold and a Non-Gaussian Limit for Compositional GPs

Mark Kozdoba, Shie Mannor

Compositional priors describe the generic properties of layered functions in deep Bayesian models, where deep neural networks with random weights are a canonical example.In the wid…

cs.LG2026

Representative Action Selection for Large Action Space Bandit Families

Quan Zhou, Mark Kozdoba, Shie Mannor

We study the problem of selecting a subset from a large action space shared by a family of bandits. In many natural situations, while the nominal set of actions is large, actions a…

cs.LG2026

Intersectional Fairness via Mixed-Integer Optimization

Jiří Němeček, Mark Kozdoba, Illia Kryvoviaz +2

The deployment of Artificial Intelligence in high-risk domains, such as finance and healthcare, necessitates models that are both fair and transparent. While regulatory frameworks,…

stat.ML2025

Efficient Fairness-Performance Pareto Front Computation

Mark Kozdoba, Binyamin Perets, Shie Mannor

There is a well known intrinsic trade-off between the fairness of a representation and the performance of classifiers derived from the representation. Due to the complexity of opti…

cs.LG2025

Bias Detection via Maximum Subgroup Discrepancy

Jiří Němeček, Mark Kozdoba, Illia Kryvoviaz +2

Bias evaluation is fundamental to trustworthy AI, both in terms of checking data quality and in terms of checking the outputs of AI systems. In testing data quality, for example, o…