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Found 5 papers, 3 papers with code
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks
In experiments, we demonstrate that the estimation results of our method have a clear and actionable interpretation and outperform conventional metrics.
Explaining Any ML Model? -- On Goals and Capabilities of XAI
We argue that this is because of a problematic reasoning scheme in XAI literature: XAI algorithms are said to complement ML models with desired properties, such as "interpretability", or "explainability".
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary
Our approach is to frame SVDD sampling as an optimization problem, where constraints guarantee that sampling indeed approximates the original decision boundary.
Active Learning of SVDD Hyperparameter Values
Existing methods to estimate hyperparameter values are purely heuristic, and the conditions under which they work well are unclear.
An Overview and a Benchmark of Active Learning for Outlier Detection with One-Class Classifiers
This article starts with a categorization of the various methods.
