Główne pojęcia
AdaTrans introduces adaptive transfer learning methods for high-dimensional regression, optimizing feature and sample-specific transfer.
Streszczenie
The content discusses the challenges of transfer learning in high-dimensional settings and proposes AdaTrans, a method that adapts to varying transferable structures. It covers feature-wise and sample-wise adaptive transfer, weight selection strategies, theoretical analysis, and empirical experiments.
- Introduction to Transfer Learning in High Dimensions
- Challenges of Negative Transfer Issue
- Feature-wise Adaptive Transfer Learning
- Sample-wise Adaptive Transfer Learning
- Data-driven Weight Selection Methods
- Empirical Experiments and Results
Statystyki
高次元線形回帰問題における次元削減の重要性を強調。
特徴ごととサンプルごとの適応的転送学習手法を提案。
既存の手法と比較して、AdaTransが優れたパフォーマンスを示す。