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» Smooth Bayesian Kernel Machines
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SSPR
2010
Springer
13 years 6 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
ACCV
2007
Springer
14 years 2 months ago
Coarse-to-Fine Statistical Shape Model by Bayesian Inference
In this paper, we take a predefined geometry shape as a constraint for accurate shape alignment. A shape model is divided in two parts: fixed shape and active shape. The fixed shap...
Ran He, Stan Z. Li, Zhen Lei, ShengCai Liao
ICML
2004
IEEE
14 years 9 months ago
Large margin hierarchical classification
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Ofer Dekel, Joseph Keshet, Yoram Singer
ESANN
2008
13 years 10 months ago
Multi-class classification of ovarian tumors
In this work, we developed classifiers to distinguish between four ovarian tumor types using Bayesian least squares support vector machines (LS-SVMs) and kernel logistic regression...
Ben Van Calster, Dirk Timmerman, Antonia C. Testa,...
JMLR
2002
137views more  JMLR 2002»
13 years 8 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
Masashi Sugiyama, Klaus-Robert Müller