Tnn: a transfer learning classifier based on weighted nearest neighbors

DOI10.1016/j.jmva.2022.105126OpenAlexW4308888929MaRDI QIDQ2101480

Guan Yu, Haiyang Sheng

Publication date: 6 December 2022

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2022.105126

zbMATH Keywords

nearest neighborbinary classificationtransfer learningminimax optimalnon-parametric classification

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05)

Uses Software

• OpenStreetMap

Cites Work

• Unnamed Item
• Direct importance estimation for covariate shift adaptation
• Classification in general finite dimensional spaces with the \(k\)-nearest neighbor rule
• Optimal weighted nearest neighbour classifiers
• Fast learning rates for plug-in classifiers
• Consistent nonparametric regression. Discussion
• Improving predictive inference under covariate shift by weighting the log-likelihood function
• Optimal aggregation of classifiers in statistical learning.
• Marginal singularity and the benefits of labels in covariate-shift
• Adaptive transfer learning
• Transfer learning for nonparametric classification: minimax rate and adaptive classifier
• On the rate of convergence of nearest neighbor rules (Corresp.)
• Sample Selection Bias as a Specification Error
• Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression
• Benefit of Interpolation in Nearest Neighbor Algorithms

This page was built for publication: Tnn: a transfer learning classifier based on weighted nearest neighbors