ResearchTrend.AI
Learning Output Kernels for Multi-Task Problems

Learning Output Kernels for Multi-Task Problems

Francesco Dinuzzo
ArXivPDFHTML

Papers citing "Learning Output Kernels for Multi-Task Problems"

7 / 7 papers shown
Title
Theoretical Models of Learning to Learn
Theoretical Models of Learning to Learn
Jonathan Baxter
22
724
0
27 Feb 2020
The representer theorem for Hilbert spaces: a necessary and sufficient condition
The representer theorem for Hilbert spaces: a necessary and sufficient condition
Francesco Dinuzzo
Bernhard Schölkopf
53
87
0
09 May 2012
A Convex Formulation for Learning Task Relationships in Multi-Task Learning
A Convex Formulation for Learning Task Relationships in Multi-Task Learning
Yu Zhang
Dit-Yan Yeung
84
460
0
15 Mar 2012
Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes
Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes
Bernie Wang
Roni Khardon
P. Protopapas
51
12
0
05 Mar 2012
Kernels for Vector-Valued Functions: a Review
Kernels for Vector-Valued Functions: a Review
Mauricio A. Alvarez
Lorenzo Rosasco
Neil D. Lawrence
GP
147
918
0
30 Jun 2011
Client-server multi-task learning from distributed datasets
Client-server multi-task learning from distributed datasets
Francesco Dinuzzo
G. Pillonetto
G. Nicolao
64
33
0
22 Dec 2008
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
Jacob D. Abernethy
Francis R. Bach
Theodoros Evgeniou
Jean-Philippe Vert
158
261
0
11 Feb 2008