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» Geometric Neural Networks and Support Multi-Vector Machines
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IJCNN
2007
IEEE
15 years 4 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
63
Voted
IJCNN
2008
IEEE
15 years 4 months ago
Ranking and selecting clustering algorithms using a meta-learning approach
Abstract— We present a novel framework that applies a metalearning approach to clustering algorithms. Given a dataset, our meta-learning approach provides a ranking for the candi...
Marcílio Carlos Pereira de Souto, Ricardo B...
77
Voted
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
15 years 10 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
BMCBI
2008
137views more  BMCBI 2008»
14 years 9 months ago
A dynamic Bayesian network approach to protein secondary structure prediction
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
Xin-Qiu Yao, Huaiqiu Zhu, Zhen-Su She
76
Voted
IJCNN
2006
IEEE
15 years 3 months ago
P-SVM Variable Selection for Discovering Dependencies Between Genetic and Brain Imaging Data
— The joint analysis of genetic and brain imaging data is the key to understand the genetic underpinnings of brain dysfunctions in several psychiatric diseases known to have a st...
Johannes Mohr, Imke Puis, Jana Wrase, Sepp Hochrei...