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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 71–80 of 97 papers

TitleStatusHype
Network Modeling and Pathway Inference from Incomplete Data ("PathInf")—0
Coverage-Based Designs Improve Sample Mining and Hyper-Parameter OptimizationCode0
Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints—0
Data Summarization at Scale: A Two-Stage Submodular Approach—0
A Mixed Hierarchical Attention based Encoder-Decoder Approach for Standard Table SummarizationCode0
Differentiable Submodular Maximization—0
Fair and Diverse DPP-based Data SummarizationCode0
An Online Algorithm for Nonparametric CorrelationsCode0
Interactive Submodular Bandit—0
One-Shot Coresets: The Case of k-Clustering—0
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