The widespread usage of machine learning systems and econometric methods in the credit
domain has transformed the decision-making process for evaluating loan applications …

Automated decision systems (ADS) are increasingly used for consequential decision-
making. These systems often rely on sophisticated yet opaque machine learning models …

Many existing fairness criteria for machine learning involve equalizing some metric across
protected groups such as race or gender. However, practitioners trying to audit or enforce …

In many classification tasks there is a requirement of monotonicity. Concretely, if all else
remains constant, increasing (resp. ádecreasing) the value of one or more features must not …

Background Total knee arthroplasty (TKA) is one of the most resource-intensive, high-
volume surgical procedures. Two drivers of the cost of TKAs are duration of surgery (DOS) …

The field of AI safety aims to prevent increasingly capable artificially intelligent systems from
causing humans harm. Research on moral alignment is widely thought to offer a promising …

The accuracy and reliability of XAI methods are important to establish their credibility and
use in complex decision-making tasks. Existing XAI methods provide little information about …

We present fast implementations of linear interpolation operators for piecewise linear
functions and multi-dimensional look-up tables. These operators are common for efficient …

In today's digital landscape, recommender systems have gained ubiquity as a means of
directing users toward personalized products, services, and content. However, despite their …

Partially monotone regression is a regression analysis in which the target values are
monotonically increasing with respect to a subset of input features. The TensorFlow Lattice …