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» Kernels for Multi--task Learning
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118
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ICML
2004
IEEE
16 years 3 months ago
Unifying collaborative and content-based filtering
Collaborative and content-based filtering are two paradigms that have been applied in the context of recommender systems and user preference prediction. This paper proposes a nove...
Justin Basilico, Thomas Hofmann
136
Voted
ALT
2006
Springer
15 years 11 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
127
Voted
IJCNN
2006
IEEE
15 years 8 months ago
Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...
Gavin C. Cawley
112
Voted
NIPS
2001
15 years 3 months ago
Quantizing Density Estimators
We suggest a nonparametric framework for unsupervised learning of projection models in terms of density estimation on quantized sample spaces. The objective is not to optimally re...
Peter Meinicke, Helge Ritter
129
Voted
ICCV
2009
IEEE
14 years 12 months ago
Bayesian Poisson regression for crowd counting
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
Antoni B. Chan, Nuno Vasconcelos