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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 1–50 of 97 papers

TitleStatusHype
Get Rid of Isolation: A Continuous Multi-task Spatio-Temporal Learning FrameworkCode1
ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short SummariesCode1
Submodlib: A Submodular Optimization LibraryCode1
Sequential estimation of Spearman rank correlation using Hermite series estimatorsCode1
Very Fast Streaming Submodular Function MaximizationCode1
Semi-supervised Batch Active Learning via Bilevel OptimizationCode1
Flexible Dataset Distillation: Learn Labels Instead of ImagesCode1
CO-Optimal TransportCode1
Scalability vs. Utility: Do We Have to Sacrifice One for the Other in Data Importance Quantification?Code1
Soft-Label Dataset Distillation and Text Dataset DistillationCode1
Sequential Quantiles via Hermite Series Density EstimationCode1
PCA-Guided Quantile Sampling: Preserving Data Structure in Large-Scale Subsampling—0
AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges—0
Dynamic data summarization for hierarchical spatial clustering—0
Fair Clustering for Data Summarization: Improved Approximation Algorithms and Complexity Insights—0
Linear Submodular Maximization with Bandit Feedback—0
GIST: Greedy Independent Set Thresholding for Diverse Data Summarization—0
Federated Combinatorial Multi-Agent Multi-Armed Bandits—0
LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces—0
GreedyML: A Parallel Algorithm for Maximizing Constrained Submodular Functions—0
DiffRed: Dimensionality Reduction guided by stable rankCode0
Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach—0
Dynamic Non-monotone Submodular Maximization—0
Dynamic Spatio-Temporal Summarization using Information Based Fusion—0
Robust Approximation Algorithms for Non-monotone k-Submodular Maximization under a Knapsack Constraint—0
Data Summarization beyond Monotonicity: Non-monotone Two-Stage Submodular Maximization—0
Time-to-Pattern: Information-Theoretic Unsupervised Learning for Scalable Time Series SummarizationCode0
On the Usefulness of Synthetic Tabular Data Generation—0
Achieving Long-term Fairness in Submodular Maximization through Randomization—0
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
Operations for Autonomous Spacecraft—0
NNK-Means: Data summarization using dictionary learning with non-negative kernel regression—0
Towards General Robustness to Bad Training Data—0
Data Summarization via Bilevel Optimization—0
A Unified Framework for Task-Driven Data Quality Management—0
Adaptive Sampling for Fast Constrained Maximization of Submodular Function—0
Synthetic Dataset Generation of Driver TelematicsCode0
Introduction to Core-sets: an Updated Survey—0
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
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