Yingyan Zeng

2 accepted papers

2026

Beyond Euclidean Summaries: Online Change Point Detection for Distribution-Valued Data

ICML 2026poster

Existing online change-point detection (CPD) methods rely on fixed-dimensional Euclidean summaries, implicitly assuming that distributional changes are well captured by moment-based or feature-based representations. They can obscure important changes in distributional shape or geometry. We propose a…

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2026

Hierarchical Dataset Selection for High-Quality Data Sharing

Xiaona Zhou, Yingyan Zeng, Ran Jin, Ismini Lourentzou

AAAI 2026technical

The success of modern machine learning hinges on access to high-quality training data. In many real-world scenarios, such as acquiring data from public repositories or sharing across institutions, data is naturally organized into discrete datasets that vary in relevance, quality, and utility. Select

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