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» Training Methods for Adaptive Boosting of Neural Networks
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IDA
2010
Springer
15 years 2 months ago
Multi-dimensional data construction method with its application to learning from small-sample-sets
Insufficient training data is one of the major problems in neural network learning, because it leads to poor learning performance. In order to enhance an intelligent learning proc...
Hsiao-Fan Wang, Chun-Jung Huang
CIKM
2008
Springer
15 years 6 months ago
AdaSum: an adaptive model for summarization
Topic representation mismatch is a key problem in topic-oriented summarization for the specified topic is usually too short to understand/interpret. This paper proposes a novel ad...
Jin Zhang, Xueqi Cheng, Gaowei Wu, Hongbo Xu
161
Voted
ICMCS
2007
IEEE
180views Multimedia» more  ICMCS 2007»
15 years 4 months ago
Content-Based Image Categorization and Retrieval using Neural Networks
We propose a neural network based method for organizing images for content-based image retrieval. We use spectral histogram features, the histograms of filtered images to capture...
Yuhua Zhu, Xiuwen Liu, Washington Mio
FOCS
2010
IEEE
15 years 2 months ago
Boosting and Differential Privacy
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
Cynthia Dwork, Guy N. Rothblum, Salil P. Vadhan
ICCS
2007
Springer
15 years 10 months ago
Neural Networks for Predicting the Behavior of Preconditioned Iterative Solvers
We evaluate the effectiveness of neural networks as a tool for predicting whether a particular combination of preconditioner and iterative method will correctly solve a given spar...
America Holloway, Tzu-Yi Chen