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» Learning from Multiple Sources of Inaccurate Data
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ICANN
2009
Springer
15 years 10 months ago
Using Kernel Basis with Relevance Vector Machine for Feature Selection
This paper presents an application of multiple kernels like Kernel Basis to the Relevance Vector Machine algorithm. The framework of kernel machines has been a source of many works...
Frederic Suard, David Mercier
135
Voted
GECCO
2010
Springer
200views Optimization» more  GECCO 2010»
15 years 8 months ago
Multivariate multi-model approach for globally multimodal problems
This paper proposes an estimation of distribution algorithm (EDA) aiming at addressing globally multimodal problems, i.e., problems that present several global optima. It can be r...
Chung-Yao Chuang, Wen-Lian Hsu
113
Voted
NGC
2001
Springer
116views Communications» more  NGC 2001»
15 years 8 months ago
Scalable IP Multicast Sender Access Control for Bi-directional Trees
Bi-directional shared tree is an efficient routing scheme for interactive multicast applications with multiple sources. Given the open-group IP multicast service model, it is impor...
Ning Wang, George Pavlou
143
Voted
MIDDLEWARE
2010
Springer
15 years 2 months ago
FaReCast: Fast, Reliable Application Layer Multicast for Flash Dissemination
Abstract. To disseminate messages from a single source to a large number of targeted receivers, a natural approach is the tree-based application layer multicast (ALM). However, in ...
Kyungbaek Kim, Sharad Mehrotra, Nalini Venkatasubr...
124
Voted
KDD
2007
ACM
190views Data Mining» more  KDD 2007»
16 years 4 months ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith