Learnability-Guided Diffusion for Dataset Distillation
Learnability-Guided Diffusion for Dataset Distillation explores A learnability-guided diffusion method for dataset distillation that reduces redundancy and improves model training efficiency.. Commercial viability score: 7/10 in Dataset Distillation.
Updated 23 hours ago
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisGrounding and Enhancing Informativeness and Utility in Dataset DistillationViability: 5.0
- Builds On ThisDataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear TasksViability: 3.0
- Builds On ThisA Survey of On-Policy Distillation for Large Language ModelsViability: 2.0
- Prior WorkBeyond Dataset Distillation: Lossless Dataset Concentration via Diffusion-Assisted Distribution AlignmentViability: 7.0
- Prior WorkAccelerating Large-Scale Dataset Distillation via Exploration-Exploitation Optimization
Related Resources
- What are the limitations of existing dataset distillation methods focusing on sample reduction?(question)
- Here are 30-50 long-tail search questions for the topic of Dataset Distillation, based on the provided context:(question)
- How can dataset distillation improve deep learning model training efficiency?(question)