We study the problem of $(\epsilon,\delta) $-certified machine unlearning for minimax
models. Most of the existing works focus on unlearning from standard statistical learning …

The Shapley value provides a unique approach to equitably gauge each player's
contribution within a coalition and has extensive applications with various utility functions. In …

With the development of AI-Generated Content (AIGC), data is becoming increasingly
important, while the right of data to be forgotten, which is defined in the General Data …

The Shapley value has been extensively used in many fields as the unique metric to fairly
evaluate player contributions in cooperative settings. Since the exact computation of …

Federated Learning (FL) provides a privacy-preserving and decentralized approach to
collaborative machine learning for multiple FL clients. The contribution estimation …

Recently, the Shapley value, a concept rooted in cooperative game theory, has found more
and more applications in databases and machine learning. Due to its combinatoric nature …

Data is the new oil of the 21st century. The growing trend of trading data for greater welfare
has led to the emergence of data markets. A data market is any mechanism whereby the …

The widespread adoption of AI-Generated Content (AIGC) has captured remarkable
interests from academia and industry. However, this advancement brings forth challenges in …

Artificial intelligence (AI) model services offer remarkable efficiency and automation,
engaging customers across various tasks. However, not all AI consumers possess sufficient …

Driven by the growing field of data intelligence, data market emerges as a promising
paradigm for data exchange, enabling the full utilization of data. Data pricing is an essential …