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ICML
2005
IEEE
16 years 7 months ago
Hierarchic Bayesian models for kernel learning
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Mark Girolami, Simon Rogers
NIPS
2003
15 years 8 months ago
Online Learning of Non-stationary Sequences
We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. We derive upper and lower relative loss bounds for a cla...
Claire Monteleoni, Tommi Jaakkola
175
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COLT
1993
Springer
15 years 10 months ago
Parameterized Learning Complexity
We describe three applications in computational learning theory of techniques and ideas recently introduced in the study of parameterized computational complexity. (1) Using param...
Rodney G. Downey, Patricia A. Evans, Michael R. Fe...
ICIP
2003
IEEE
16 years 8 months ago
Image retrieval with SVM active learning embedding Euclidean search
Image retrieval with relevance feedback suffers from the small sample problem. Recently, SVM active learning has been proposed to tackle this problem, showing promising results. H...
Lei Wang, Kap Luk Chan, Yap Peng Tan
ILP
2005
Springer
16 years 3 days ago
Online Closure-Based Learning of Relational Theories
Online learning algorithms such as Winnow have received much attention in Machine Learning. Their performance degrades only logarithmically with the input dimension, making them us...
Frédéric Koriche