Summary of Fale: Fairness-aware Ale Plots For Auditing Bias in Subgroups, by Giorgos Giannopoulos et al.
FALE: Fairness-Aware ALE Plots for Auditing Bias in Subgroupsby Giorgos Giannopoulos, Dimitris Sacharidis, Nikolas Theologitis,…
FALE: Fairness-Aware ALE Plots for Auditing Bias in Subgroupsby Giorgos Giannopoulos, Dimitris Sacharidis, Nikolas Theologitis,…
Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plotsby…
Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networksby Fanghui Liu, Leello Dadi, Volkan CevherFirst submitted…
Harmonic Machine Learning Models are Robustby Nicholas S. Kersting, Yi Li, Aman Mohanty, Oyindamola Obisesan,…
Learning Mixtures of Gaussians Using Diffusion Modelsby Khashayar Gatmiry, Jonathan Kelner, Holden LeeFirst submitted to…
Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-ADby Valentina…
Bridging Data Barriers among Participants: Assessing the Potential of Geoenergy through Federated Learningby Weike Peng,…
Solving Partial Differential Equations with Equivariant Extreme Learning Machinesby Hans Harder, Jean Rabault, Ricardo Vinuesa,…
Learning Governing Equations of Unobserved States in Dynamical Systemsby Gevik Grigorian, Sandip V. George, Simon…
Terrain characterisation for online adaptability of automated sonar processing: Lessons learnt from operationally applying ATR…