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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 1–10 of 97 papers

TitleStatusHype
PCA-Guided Quantile Sampling: Preserving Data Structure in Large-Scale Subsampling—0
AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges—0
Dynamic data summarization for hierarchical spatial clustering—0
Fair Clustering for Data Summarization: Improved Approximation Algorithms and Complexity Insights—0
Get Rid of Isolation: A Continuous Multi-task Spatio-Temporal Learning FrameworkCode1
Linear Submodular Maximization with Bandit Feedback—0
GIST: Greedy Independent Set Thresholding for Diverse Data Summarization—0
Federated Combinatorial Multi-Agent Multi-Armed Bandits—0
LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces—0
GreedyML: A Parallel Algorithm for Maximizing Constrained Submodular Functions—0
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