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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
Semi-supervised Batch Active Learning via Bilevel OptimizationCode1
Deep Submodular Networks for Extractive Data Summarization—0
Fair and Representative Subset Selection from Data StreamsCode0
A Principled Approach to Data Valuation for Federated Learning—0
β-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of OutliersCode0
Fast and Private Submodular and k-Submodular Functions Maximization with Matroid Constraints—0
Understanding collections of related datasets using dependent MMD coresetsCode0
Flexible Dataset Distillation: Learn Labels Instead of ImagesCode1
Deuteros 2.0: Peptide-level significance testing of data from hydrogen deuterium exchange mass spectrometryCode0
Non-Adaptive Adaptive Sampling on Turnstile Streams—0
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