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» Efficient Model Selection for Kernel Logistic Regression
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NN
2000
Springer
165views Neural Networks» more  NN 2000»
15 years 7 days 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
104
Voted
QRE
2008
140views more  QRE 2008»
14 years 12 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 ...
111
Voted
SIGIR
2008
ACM
15 years 11 days 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
16 years 1 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
112
Voted
ICIP
2006
IEEE
16 years 2 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