16 citations · 17 across the 5 of their papers we have counts for
6 papers
Dissecting Performative Prediction: A Comprehensive Survey
Thomas Kehrenberg, Javier Sanguino, Jose A. Lozano +1
The field of performative prediction had its beginnings in 2020 with the seminal paper "Performative Prediction" by Perdomo et al., which established a novel machine learning setup…
Strategically Deceptive Model Deployment in Performative Prediction
Javier Sanguino Bautiste, Thomas Kehrenberg, Jose A. Lozano +1
Machine Learning systems are increasingly deployed in decision-making settings that shape user behavior and, in turn, the data on which future decisions are based. Performative Pre…
Addressing Missing Sources with Adversarial Support-Matching
Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska +1
When trained on diverse labeled data, machine learning models have proven themselves to be a powerful tool in all facets of society. However, due to budget limitations, deliberate…
Null-sampling for Interpretable and Fair Representations
Thomas Kehrenberg, Myles Bartlett, Oliver Thomas +1
We propose to learn invariant representations, in the data domain, to achieve interpretability in algorithmic fairness. Invariance implies a selectivity for high level, relevant co…
Tuning Fairness by Balancing Target Labels
Thomas Kehrenberg, Zexun Chen, Novi Quadrianto
The issue of fairness in machine learning models has recently attracted a lot of attention as ensuring it will ensure continued confidence of the general public in the deployment o…
Weakly Supervised One-Shot Detection with Attention Similarity Networks
Gil Keren, Maximilian Schmitt, Thomas Kehrenberg +1
Neural network models that are not conditioned on class identities were shown to facilitate knowledge transfer between classes and to be well-suited for one-shot learning tasks. Fo…