Multi-output learning via spectral filtering

DOI10.1007/s10994-012-5282-yzbMath1243.68233OpenAlexW2148901023WikidataQ62660639 ScholiaQ62660639MaRDI QIDQ439000

Lorenzo Rosasco, Alessandro Verri, Luca Baldassarre, Annalisa Barla

Publication date: 31 July 2012

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-012-5282-y

zbMATH Keywords

regularizationvector-valued functionskernel methodsmulti-taskspectral filtering

Mathematics Subject Classification ID

Computational learning theory (68Q32) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (5)

Unnamed Item ⋮ Multi-target prediction: a unifying view on problems and methods ⋮ Operator-valued kernel-based vector autoregressive models for network inference ⋮ A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression ⋮ Regularized vector field learning with sparse approximation for mismatch removal

Uses Software

• Caltech-256
• PRMLT

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Model selection for regularized least-squares algorithm in learning theory
• On regularization algorithms in learning theory
• Convex multi-task feature learning
• From basis functions to basis fields: Vector field approximation from sparse data
• Reduced-rank regression for the multivariate linear model
• Interpolation of spatial data. Some theory for kriging
• A density theorem for matrix-valued radial basis functions
• Least angle regression. (With discussion)
• Optimal rates for the regularized least-squares algorithm
• Sous-espaces d'espaces vectoriels topologiques et noyaux associés. (Noyaux reproduisants.)
• 10.1162/153244302760185252
• The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses
• VECTOR VALUED REPRODUCING KERNEL HILBERT SPACES OF INTEGRABLE FUNCTIONS AND MERCER THEOREM
• Spectral Algorithms for Supervised Learning
• A BERRY-ESSEEN TYPE BOUND OF REGRESSION ESTIMATOR BASED ON LINEAR PROCESS ERRORS
• Multivariate regression analysis and canonical variates
• Generalized Hermite Interpolation Via Matrix-Valued Conditionally Positive Definite Functions
• Boosting With theL₂Loss
• 10.1162/153244302760200704
• MODULI OF CONTINUITY FOR OPERATOR VALUED FUNCTIONS
• 10.1162/153244304322765658
• Multitask Learning with Expert Advice
• Learning Theory
• Multicategory Support Vector Machines
• On Learning Vector-Valued Functions
• The elements of statistical learning. Data mining, inference, and prediction

This page was built for publication: Multi-output learning via spectral filtering