SOTAVerified

Dataset Condensation

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–50 of 56 papers

TitleStatusHype
Multisize Dataset CondensationCode1
CAFE: Learning to Condense Dataset by Aligning FeaturesCode1
Condensing Graphs via One-Step Gradient MatchingCode1
CondTSF: One-line Plugin of Dataset Condensation for Time Series ForecastingCode1
Dataset Condensation for Time Series Classification via Dual Domain MatchingCode1
Dataset Condensation via Efficient Synthetic-Data ParameterizationCode1
Dataset Condensation with Contrastive SignalsCode1
Dataset Condensation with Distribution MatchingCode1
Dataset Condensation with Gradient MatchingCode1
DC-BENCH: Dataset Condensation BenchmarkCode1
Distilling Datasets Into Less Than One ImageCode1
M3D: Dataset Condensation by Minimizing Maximum Mean DiscrepancyCode1
Efficient Dataset Distillation Using Random Feature ApproximationCode1
Elucidating the Design Space of Dataset CondensationCode1
Generalized Large-Scale Data Condensation via Various Backbone and Statistical MatchingCode1
Improved Distribution Matching for Dataset CondensationCode1
A Large-Scale Study on Video Action Dataset CondensationCode1
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New PerspectiveCode1
Synthesizing Informative Training Samples with GANCode1
Towards Model-Agnostic Dataset Condensation by Heterogeneous ModelsCode1
You Only Condense Once: Two Rules for Pruning Condensed DatasetsCode1
Connect the dots: Dataset Condensation, Differential Privacy, and Adversarial Uncertainty—0
Robustness-preserving Lifelong Learning via Dataset Condensation—0
SCORE: Soft Label Compression-Centric Dataset Condensation via Coding Rate Optimization—0
Slimmable Dataset Condensation—0
Spectral Greedy Coresets for Graph Neural Networks—0
Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation—0
TF-DCon: Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation—0
Dataset Condensation via Generative Model—0
Towards Efficient Deep Hashing Retrieval: Condensing Your Data via Feature-Embedding Matching—0
Enhancing Generalization via Sharpness-Aware Trajectory Matching for Dataset Condensation—0
No Free Lunch in "Privacy for Free: How does Dataset Condensation Help Privacy"—0
Revisiting Permutation Symmetry for Merging Models between Different Datasets—0
Dataset Condensation with Latent Quantile Matching—0
When less is more: Simplifying inputs aids neural network understanding—0
Video Dataset Condensation with Diffusion Models—0
DCFL: Non-IID awareness Data Condensation aided Federated Learning—0
Diffusion-Augmented Coreset Expansion for Scalable Dataset Distillation—0
Diffusion Dataset Condensation: Training Your Diffusion Model Faster with Less Data—0
Calibrated Dataset Condensation for Faster Hyperparameter Search—0
Medical records condensation: a roadmap towards healthcare data democratisation—0
Koopcon: A new approach towards smarter and less complex learning—0
Dataset Condensation with Latent Space Knowledge Factorization and SharingCode0
Decomposed Distribution Matching in Dataset CondensationCode0
Delving into Effective Gradient Matching for Dataset CondensationCode0
Fast Graph Condensation with Structure-based Neural Tangent KernelCode0
Mitigating Bias in Dataset DistillationCode0
Bi-Directional Multi-Scale Graph Dataset Condensation via Information BottleneckCode0
Is Adversarial Training with Compressed Datasets Effective?Code0
Bayesian Pseudo-Coresets via Contrastive DivergenceCode0
Show:102550
← PrevPage 1 of 2Next →

No leaderboard results yet.