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Data Summarization

Data Summarization is a central problem in the area of machine learning, where we want to compute a small summary of the data.

Source: How to Solve Fair k-Center in Massive Data Models

Papers

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Showing 81–90 of 97 papers

TitleStatusHype
Scalable k-Means Clustering via Lightweight Coresets—0
A Principled Approach to Data Valuation for Federated Learning—0
An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms—0
Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach—0
Achieving Long-term Fairness in Submodular Maximization through Randomization—0
Data Summarization beyond Monotonicity: Non-monotone Two-Stage Submodular Maximization—0
Data Summarization via Bilevel Optimization—0
Deep Submodular Networks for Extractive Data Summarization—0
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten"—0
Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach—0
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