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Dataset Condensation

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

Papers

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Showing 26–50 of 56 papers

TitleStatusHype
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
Dataset Condensation with Latent Quantile Matching—0
Mitigating Bias in Dataset DistillationCode0
DANCE: Dual-View Distribution Alignment for Dataset CondensationCode0
Spectral Greedy Coresets for Graph Neural Networks—0
Calibrated Dataset Condensation for Faster Hyperparameter Search—0
Koopcon: A new approach towards smarter and less complex learning—0
Connect the dots: Dataset Condensation, Differential Privacy, and Adversarial Uncertainty—0
Is Adversarial Training with Compressed Datasets Effective?Code0
Dataset Condensation Driven Machine UnlearningCode0
DCFL: Non-IID awareness Data Condensation aided Federated Learning—0
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
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
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