research
∙
02/15/2023
Evaluating Trade-offs in Computer Vision Between Attribute Privacy, Fairness and Utility
This paper investigates to what degree and magnitude tradeoffs exist bet...
share
research
∙
10/26/2022
Addressing Heterogeneity in Federated Learning via Distributional Transformation
Federated learning (FL) allows multiple clients to collaboratively train...
research
∙
06/20/2022
Achieving Utility, Fairness, and Compactness via Tunable Information Bottleneck Measures
Designing machine learning algorithms that are accurate yet fair, not di...
research
∙
03/09/2022
Renyi Fair Information Bottleneck for Image Classification
We develop a novel method for ensuring fairness in machine learning whic...
research
∙
03/03/2022
Robustness and Adaptation to Hidden Factors of Variation
We tackle here a specific, still not widely addressed aspect, of AI robu...
research
∙
02/28/2022
EdgeMixup: Improving Fairness for Skin Disease Classification and Segmentation
Skin lesions can be an early indicator of a wide range of infectious and...
research
∙
08/16/2021
Patch Attack Invariance: How Sensitive are Patch Attacks to 3D Pose?
Perturbation-based attacks, while not physically realizable, have been t...
research
∙
07/28/2021
Generalizing Fairness: Discovery and Mitigation of Unknown Sensitive Attributes
Ensuring trusted artificial intelligence (AI) in the real world is an cr...
research
∙
01/05/2021
Practical Blind Membership Inference Attack via Differential Comparisons
Membership inference (MI) attacks affect user privacy by inferring wheth...
research
∙
12/11/2020
Objectness-Guided Open Set Visual Search and Closed Set Detection
Searching for small objects in large images is currently challenging for...
research
∙
12/11/2020
Random Projections for Adversarial Attack Detection
Whilst adversarial attack detection has received considerable attention,...
research
∙
06/03/2020
Rényi Generative Adversarial Networks
We propose a loss function for generative adversarial networks (GANs) us...
research
∙
05/01/2020
Jacks of All Trades, Masters Of None: Addressing Distributional Shift and Obtrusiveness via Transparent Patch Attacks
We focus on the development of effective adversarial patch attacks and –...
research
∙
04/28/2020
Addressing Artificial Intelligence Bias in Retinal Disease Diagnostics
Few studies of deep learning systems (DLS) have addressed issues of arti...
research
∙
02/25/2020
Unsupervised Semantic Attribute Discovery and Control in Generative Models
This work focuses on the ability to control via latent space factors sem...
research
∙
03/06/2018
