47 citations · 99 across the 17 of their papers we have counts for
8 papers · 1 filter
Efficient Contrastive Explanations on Demand
Yacine Izza, Joao Marques-Silva
Recent work revealed a tight connection between adversarial robustness and restricted forms of symbolic explanations, namely distance-based (formal) explanations. This connection i…
Distance-Restricted Explanations: Theoretical Underpinnings & Efficient Implementation
Yacine Izza, Xuanxiang Huang, Antonio Morgado +3
The uses of machine learning (ML) have snowballed in recent years. In many cases, ML models are highly complex, and their operation is beyond the understanding of human decision-ma…
The Pros and Cons of Adversarial Robustness
Yacine Izza, Joao Marques-Silva
Robustness is widely regarded as a fundamental problem in the analysis of machine learning (ML) models. Most often robustness equates with deciding the non-existence of adversarial…
Locally-Minimal Probabilistic Explanations
Yacine Izza, Kuldeep S. Meel, Joao Marques-Silva
Explainable Artificial Intelligence (XAI) is widely regarding as a cornerstone of trustworthy AI. Unfortunately, most work on XAI offers no guarantees of rigor. In high-stakes doma…
On Computing Relevant Features for Explaining NBCs
Yacine Izza, Joao Marques-Silva
Despite the progress observed with model-agnostic explainable AI (XAI), it is the case that model-agnostic XAI can produce incorrect explanations. One alternative are the so-called…
Efficient Explanations With Relevant Sets
Yacine Izza, Alexey Ignatiev, Nina Narodytska +2
Recent work proposed -relevant inputs (or sets) as a probabilistic explanation for the predictions made by a classifier on a given input. -relevant sets are significant becau…