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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 51–97 of 97 papers

TitleStatusHype
Lazier Than Lazy Greedy—0
Less is More: Learning Prominent and Diverse Topics for Data Summarization—0
Leveraging Sparsity for Efficient Submodular Data Summarization—0
Linear Relaxations for Finding Diverse Elements in Metric Spaces—0
Linear Submodular Maximization with Bandit Feedback—0
LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces—0
Max-Min Diversification with Fairness Constraints: Exact and Approximation Algorithms—0
Network Modeling and Pathway Inference from Incomplete Data ("PathInf")—0
NNK-Means: Data summarization using dictionary learning with non-negative kernel regression—0
Non-Adaptive Adaptive Sampling on Turnstile Streams—0
One-Shot Coresets: The Case of k-Clustering—0
On the Usefulness of Synthetic Tabular Data Generation—0
PCA-Guided Quantile Sampling: Preserving Data Structure in Large-Scale Subsampling—0
Operations for Autonomous Spacecraft—0
Real-Time EEG Classification via Coresets for BCI Applications—0
Regularized Submodular Maximization at Scale—0
Robust Approximation Algorithms for Non-monotone k-Submodular Maximization under a Knapsack Constraint—0
Robust Submodular Maximization: A Non-Uniform Partitioning Approach—0
Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints—0
Adaptive Sampling for Fast Constrained Maximization of Submodular Function—0
Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach—0
Coresets for Vector Summarization with Applications to Network Graphs—0
Streaming Submodular Maximization under a k-Set System Constraint—0
Data Summarization at Scale: A Two-Stage Submodular Approach—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
MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart DerenderingCode0
Scalable k-Means Clustering via Lightweight CoresetsCode0
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
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