SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–97 of 97 papers

TitleStatusHype
Coresets for Vector Summarization with Applications to Network Graphs—0
Group Equality in Adaptive Submodular MaximizationCode0
A Mixed Hierarchical Attention based Encoder-Decoder Approach for Standard Table SummarizationCode0
An Online Algorithm for Nonparametric CorrelationsCode0
Understanding collections of related datasets using dependent MMD coresetsCode0
apricot: Submodular selection for data summarization in PythonCode0
Balancing Utility and Fairness in Submodular Maximization (Technical Report)Code0
β-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of OutliersCode0
Black-box Coreset Variational InferenceCode0
Coverage-Based Designs Improve Sample Mining and Hyper-Parameter OptimizationCode0
Deuteros 2.0: Peptide-level significance testing of data from hydrogen deuterium exchange mass spectrometryCode0
DiffRed: Dimensionality Reduction guided by stable rankCode0
Fair and Diverse DPP-based Data SummarizationCode0
Fair k-Center Clustering for Data SummarizationCode0
Fast and Accurate Least-Mean-Squares SolversCode0
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer VisionCode0
Streaming Algorithms for Diversity Maximization with Fairness ConstraintsCode0
Streaming Submodular Maximization under a k-Set System ConstraintCode0
Fair and Representative Subset Selection from Data StreamsCode0
Synthetic Dataset Generation of Driver TelematicsCode0
Time-to-Pattern: Information-Theoretic Unsupervised Learning for Scalable Time Series SummarizationCode0
Towards Neural Numeric-To-Text Generation From Temporal Personal Health DataCode0
Show:102550
← PrevPage 4 of 4Next →

No leaderboard results yet.