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Dataset Condensation

Condense the full dataset into a tiny set of synthetic data.

Papers

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Showing 1–50 of 56 papers

TitleStatusHype
Diffusion Dataset Condensation: Training Your Diffusion Model Faster with Less Data—0
Video Dataset Condensation with Diffusion Models—0
SCORE: Soft Label Compression-Centric Dataset Condensation via Coding Rate Optimization—0
Enhancing Generalization via Sharpness-Aware Trajectory Matching for Dataset Condensation—0
A Large-Scale Study on Video Action Dataset CondensationCode1
Bi-Directional Multi-Scale Graph Dataset Condensation via Information BottleneckCode0
Decomposed Distribution Matching in Dataset CondensationCode0
Diffusion-Augmented Coreset Expansion for Scalable Dataset Distillation—0
Towards Model-Agnostic Dataset Condensation by Heterogeneous ModelsCode1
Dataset Condensation with Latent Quantile Matching—0
Mitigating Bias in Dataset DistillationCode0
CondTSF: One-line Plugin of Dataset Condensation for Time Series ForecastingCode1
DANCE: Dual-View Distribution Alignment for Dataset CondensationCode0
Calibrated Dataset Condensation for Faster Hyperparameter Search—0
Spectral Greedy Coresets for Graph Neural Networks—0
Koopcon: A new approach towards smarter and less complex learning—0
Elucidating the Design Space of Dataset CondensationCode1
Distilling Datasets Into Less Than One ImageCode1
Dataset Condensation for Time Series Classification via Dual Domain MatchingCode1
Multisize Dataset CondensationCode1
Connect the dots: Dataset Condensation, Differential Privacy, and Adversarial Uncertainty—0
Is Adversarial Training with Compressed Datasets Effective?Code0
Dataset Condensation Driven Machine UnlearningCode0
M3D: Dataset Condensation by Minimizing Maximum Mean DiscrepancyCode1
DCFL: Non-IID awareness Data Condensation aided Federated Learning—0
Generalized Large-Scale Data Condensation via Various Backbone and Statistical MatchingCode1
You Only Condense Once: Two Rules for Pruning Condensed DatasetsCode1
Fast Graph Condensation with Structure-based Neural Tangent KernelCode0
TF-DCon: Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation—0
Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation—0
Dataset Condensation for RecommendationCode0
Dataset Condensation via Generative Model—0
Improved Distribution Matching for Dataset CondensationCode1
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New PerspectiveCode1
Revisiting Permutation Symmetry for Merging Models between Different Datasets—0
Towards Efficient Deep Hashing Retrieval: Condensing Your Data via Feature-Embedding Matching—0
Medical records condensation: a roadmap towards healthcare data democratisation—0
Bayesian Pseudo-Coresets via Contrastive DivergenceCode0
Robustness-preserving Lifelong Learning via Dataset Condensation—0
Dataset Distillation: A Comprehensive ReviewCode0
Slimmable Dataset Condensation—0
Efficient Dataset Distillation Using Random Feature ApproximationCode1
No Free Lunch in "Privacy for Free: How does Dataset Condensation Help Privacy"—0
Dataset Condensation with Latent Space Knowledge Factorization and SharingCode0
Delving into Effective Gradient Matching for Dataset CondensationCode0
DC-BENCH: Dataset Condensation BenchmarkCode1
Condensing Graphs via One-Step Gradient MatchingCode1
Privacy for Free: How does Dataset Condensation Help Privacy?Code0
Dataset Condensation via Efficient Synthetic-Data ParameterizationCode1
Synthesizing Informative Training Samples with GANCode1
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