Feature attributions based on the Shapley value are popular for explaining machine
learning models. However, their estimation is complex from both theoretical and …

Open-vocabulary models are a promising new paradigm for image classification. Unlike
traditional classification models, open-vocabulary models classify among any arbitrary set of …

Over the last few years, the Shapley value, a solution concept from cooperative game theory,
has found numerous applications in machine learning. In this paper, we first discuss …

Abstract With Artificial Intelligence advancement, Deep neural networks (DNN) are
extensively used for decision-making in intelligent systems. However, improved …

Although Shapley values are theoretically appealing for explaining black-box models, they
are costly to calculate and thus impractical in settings that involve large, high-dimensional …

Shapley values, which were originally designed to assign attributions to individual players in
coalition games, have become a commonly used approach in explainable machine learning …

Data valuation in machine learning (ML) is an emerging research area that studies the worth
of data in ML. Data valuation is used in collaborative ML to determine a fair compensation …

Recently, there has been a growing demand for the deployment of Explainable Artificial
Intelligence (XAI) algorithms in real-world applications. However, traditional XAI methods …

Recent advancements in explainable machine learning provide effective and faithful
solutions for interpreting model behaviors. However, many explanation methods encounter …

Shapley value provides a unique way to fairly assess each player's contribution in a
coalition and has enjoyed many applications. However, the exact computation of Shapley …