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» Efficient Model Selection for Kernel Logistic Regression
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NN
2000
Springer
165views Neural Networks» more  NN 2000»
13 years 7 months ago
Construction of confidence intervals for neural networks based on least squares estimation
We present the theoretical results about the construction of confidence intervals for a nonlinear regression based on least squares estimation and using the linear Taylor expansio...
Isabelle Rivals, Léon Personnaz
QRE
2008
140views more  QRE 2008»
13 years 6 months ago
Discrete mixtures of kernels for Kriging-based optimization
: Kriging-based exploration strategies often rely on a single Ordinary Kriging model which parametric covariance kernel is selected a priori or on the basis of an initial data set....
David Ginsbourger, Céline Helbert, Laurent ...
SIGIR
2008
ACM
13 years 7 months ago
A study of learning a merge model for multilingual information retrieval
This paper proposes a learning approach for the merging process in multilingual information retrieval (MLIR). To conduct the learning approach, we also present a large number of f...
Ming-Feng Tsai, Yu-Ting Wang, Hsin-Hsi Chen
ICML
2004
IEEE
14 years 8 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
ICIP
2006
IEEE
14 years 9 months ago
Robust Kernel-Based Tracking using Optimal Control
Although more efficient in computation compared to other tracking approaches such as particle filtering, the kernel-based tracking suffers from the "singularity" problem...
Wei Qu, Dan Schonfeld