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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 41–50 of 97 papers

TitleStatusHype
Fast determinantal point processes via distortion-free intermediate sampling—0
Fast Distributed Submodular Cover: Public-Private Data Summarization—0
Federated Combinatorial Multi-Agent Multi-Armed Bandits—0
Data Summarization at Scale: A Two-Stage Submodular Approach—0
Coresets for Vector Summarization with Applications to Network Graphs—0
GIST: Greedy Independent Set Thresholding for Diverse Data Summarization—0
Graph Summarization Methods and Applications: A Survey—0
GreedyML: A Parallel Algorithm for Maximizing Constrained Submodular Functions—0
AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges—0
Group Fairness in Non-monotone Submodular Maximization—0
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