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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 11–20 of 97 papers

TitleStatusHype
DiffRed: Dimensionality Reduction guided by stable rankCode0
Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach—0
Dynamic Non-monotone Submodular Maximization—0
Dynamic Spatio-Temporal Summarization using Information Based Fusion—0
Robust Approximation Algorithms for Non-monotone k-Submodular Maximization under a Knapsack Constraint—0
Data Summarization beyond Monotonicity: Non-monotone Two-Stage Submodular Maximization—0
Time-to-Pattern: Information-Theoretic Unsupervised Learning for Scalable Time Series SummarizationCode0
On the Usefulness of Synthetic Tabular Data Generation—0
ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short SummariesCode1
Achieving Long-term Fairness in Submodular Maximization through Randomization—0
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