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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 21–30 of 97 papers

TitleStatusHype
Group Fairness in Non-monotone Submodular Maximization—0
Max-Min Diversification with Fairness Constraints: Exact and Approximation Algorithms—0
MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart DerenderingCode0
Black-box Coreset Variational InferenceCode0
Balancing Utility and Fairness in Submodular Maximization (Technical Report)Code0
Streaming Algorithms for Diversity Maximization with Fairness ConstraintsCode0
Towards Neural Numeric-To-Text Generation From Temporal Personal Health DataCode0
Group Equality in Adaptive Submodular MaximizationCode0
Guided Exploration of Data Summaries—0
Submodlib: A Submodular Optimization LibraryCode1
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