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» Classification Using Multiple and Negative Target Rules
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MM
2006
ACM
152views Multimedia» more  MM 2006»
14 years 1 months ago
Multimodal fusion using learned text concepts for image categorization
Conventional image categorization techniques primarily rely on low-level visual cues. In this paper, we describe a multimodal fusion scheme which improves the image classification...
Qiang Zhu, Mei-Chen Yeh, Kwang-Ting Cheng
SIGCOMM
2010
ACM
13 years 7 months ago
EffiCuts: optimizing packet classification for memory and throughput
Packet Classification is a key functionality provided by modern routers. Previous decision-tree algorithms, HiCuts and HyperCuts, cut the multi-dimensional rule space to separate ...
Balajee Vamanan, Gwendolyn Voskuilen, T. N. Vijayk...
LCN
2006
IEEE
14 years 1 months ago
Training on multiple sub-flows to optimise the use of Machine Learning classifiers in real-world IP networks
Literature on the use of machine learning (ML) algorithms for classifying IP traffic has relied on fullflows or the first few packets of flows. In contrast, many real-world scenar...
Thuy T. T. Nguyen, Grenville J. Armitage
AI
2010
Springer
13 years 9 months ago
Improving Multiclass Text Classification with Error-Correcting Output Coding and Sub-class Partitions
Error-Correcting Output Coding (ECOC) is a general framework for multiclass text classification with a set of binary classifiers. It can not only help a binary classifier solve mul...
Baoli Li, Carl Vogel
AUTOMATICA
2010
96views more  AUTOMATICA 2010»
13 years 7 months ago
Frequency domain iterative feedforward/feedback tuning for MIMO ANVC
: A new iterative feedback/feedforward tuning (IFFT) method is presented for multiple-input multiple output (MIMO) control systems that relies on efficient computation of the negat...
Jian Luo, Sandor M. Veres