activity
20242026
collaborators

7 papers

cs.LG2026

Tractable Probabilistic Models for Investment Planning

Nicolas M. Cuadrado A., Mohannad Takrouri, Jiří Němeček +2

Investment planning in power utilities, such as generation and transmission expansion, requires decisions under substantial uncertainty over decade--long horizons for policies, dem…

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,…

cs.AI2026

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models

German M. Matilla, Jiri Nemecek, Illia Kryvoviaz +1

There is a strong recent emphasis on trustworthy AI. In particular, international regulations, such as the AI Act, demand that AI practitioners measure data quality on the input an…

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…

cs.AI2025

Generating Likely Counterfactuals Using Sum-Product Networks

Jiri Nemecek, Tomas Pevny, Jakub Marecek

The need to explain decisions made by AI systems is driven by both recent regulation and user demand. The decisions are often explainable only post hoc. In counterfactual explanati…

math.OC2024

Piecewise Polynomial Regression of Tame Functions via Integer Programming

Gilles Bareilles, Johannes Aspman, Jiri Nemecek +1

Tame functions are a class of nonsmooth, nonconvex functions, which feature in a wide range of applications: functions encountered in the training of deep neural networks with all…