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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 31–40 of 97 papers

TitleStatusHype
Group Equality in Adaptive Submodular MaximizationCode0
Time-to-Pattern: Information-Theoretic Unsupervised Learning for Scalable Time Series SummarizationCode0
Distributed Submodular Cover: Succinctly Summarizing Massive Data—0
Distributed Maximization of Submodular plus Diversity Functions for Multi-label Feature Selection on Huge Datasets—0
Differentially Private Submodular Maximization: Data Summarization in Disguise—0
Differentially Private Distributed Data Summarization under Covariate Shift—0
Differentiable Submodular Maximization—0
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten"—0
A Unified Framework for Task-Driven Data Quality Management—0
An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms—0
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