EPrints submitted by Massimiliano Pontil
Click here to see user's record. Number of EPrints submitted by this user: 19
Learning the kernel function via regularization
Massimiliano Pontil and Charles Micchelli
(2004)
Technical Report.
UCL, UK.
Regularized Multi--Task Learning
Massimiliano Pontil and Theos Evgeniou
In: KDD 2004(2004).
Learning Convex Combinations of Continuously Parameterized Basic Kernels
Andreas Argyriou, Charles Micchelli and Massimiliano Pontil
In: COLT 2005, June 2005, Bertinoro, Italy.
Online Learning over Graphs
Mark Herbster, Massimiliano Pontil and Lisa Wainer
In: ICML 2005, Bonn, Germany(2005).
Error bounds for learning the kernel
Charles Micchelli, Massimiliano Pontil, Qiang WU and Ding-Xuan Zhou
Research Note
Number 05/09,
,
2005.
Multi-Task Feature Learning
Andreas Argyriou, Theodoros Evgeniou and Massimiliano Pontil
In: NIPS 2006, Vancouver, CA(2007).
Prediction on a Graph with the Perceptron
Mark Herbster and Massimiliano Pontil
In: NIPS 2006, December 2006, Vancouver, CA.
A DC algorithm for kernel selection
Andreas Argyriou, Raphael Hauser, Charles Micchelli and Massimiliano Pontil
In: ICML 2006(2006).
Combining graph Laplacians for semi--supervised learning
Andreas Argyriou, Mark Herbster and Massimiliano Pontil
In: NIPS 2005, December, 2005, Vancouver, CA.
A Spectral Regularization Framework for Multi-Task Structure Learning
Andreas Argyriou, Charles Micchelli, Massimiliano Pontil and Yiming Ying
In: NIPS 2007, Dec 2007, Vancouver, Canada.
Universal multi-task kernels
Andreas Caponnetto, Charles Micchelli, Massimiliano Pontil and Yiming Ying
(2007)
Technical Report.
UCL.
Entropy conditions for Lr-convergence of empirical processes
Andrea Caponnetto, Ernesto De Vito and Massimiliano Pontil
(2007)
Other.
UCL.
Convex Multi-Task Feature Learning
Andreas Argyriou, Theodoros Evgeniou and Massimiliano Pontil
Machine Learning
2006.
Feature space perspectives for learning the kernel
Charles Micchelli and Massimiliano Pontil
Machine Learning
2007.
A Convex Optimization Approach to Modeling
Consumer Heterogeneity in Conjoint Estimation
Theodoros Evgeniou, Massimiliano Pontil and Olivier Toubia
Marketing Science
2007.
When is there a representer theorem? Vector versus matrix regularizers
Andreas Argyriou, Charles Micchelli and Massimiliano Pontil
Submitted to J. Mach. Learn. Research
2008.
A Uniform Lower Error Bound for Half-space Learning
Andreas Maurer and Massimiliano Pontil
In: Algorithmic Learning Theory, 13-16 Oct 2008, Budapest.
Generalization Bounds for K-Dimensional Coding Schemes in Hilbert Spaces
Andreas Maurer and Massimiliano Pontil
In: Algorithmic Learning Theory 2008, 13-16 Oct 2008, Budapest.
An Algorithm for Transfer Learning in a Heterogeneous Environment
Andreas Argyriou, Andreas Maurer and Massimiliano Pontil
In: ECML 2008(2008).
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