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» A Framework for Pattern-Based Global Models
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NIPS
1998
14 years 11 months ago
Global Optimisation of Neural Network Models via Sequential Sampling
We propose a novel strategy for training neural networks using sequential Monte Carlo algorithms. This global optimisation strategy allows us to learn the probability distribution...
João F. G. de Freitas, Mahesan Niranjan, Ar...
TCSV
2008
195views more  TCSV 2008»
14 years 9 months ago
Locality Versus Globality: Query-Driven Localized Linear Models for Facial Image Computing
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
MM
2004
ACM
124views Multimedia» more  MM 2004»
15 years 2 months ago
An online-optimized incremental learning framework for video semantic classification
This paper considers the problems of feature variation and concept uncertainty in typical learning-based video semantic classification schemes. We proposed a new online semantic c...
Jun Wu, Xian-Sheng Hua, HongJiang Zhang, Bo Zhang
ISMIS
2011
Springer
14 years 12 days ago
An Evolutionary Algorithm for Global Induction of Regression Trees with Multivariate Linear Models
In the paper we present a new evolutionary algorithm for induction of regression trees. In contrast to the typical top-down approaches it globally searches for the best tree struct...
Marcin Czajkowski, Marek Kretowski
87
Voted
WSDM
2009
ACM
140views Data Mining» more  WSDM 2009»
15 years 4 months ago
Effective latent space graph-based re-ranking model with global consistency
Recently the re-ranking algorithms have been quite popular for web search and data mining. However, one of the issues is that those algorithms treat the content and link informati...
Hongbo Deng, Michael R. Lyu, Irwin King