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AI
2002
Springer
13 years 9 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
NN
2002
Springer
115views Neural Networks» more  NN 2002»
13 years 9 months ago
A self-organising network that grows when required
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow
ICDT
2007
ACM
121views Database» more  ICDT 2007»
14 years 4 months ago
Compact Samples for Data Dissemination
We consider data dissemination in a peer-to-peer network, where each user wishes to obtain some subset of the available information objects. In most of the modern algorithms for su...
Tova Milo, Assaf Sagi, Elad Verbin
DATAMINE
2006
224views more  DATAMINE 2006»
13 years 10 months ago
Characteristic-Based Clustering for Time Series Data
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
MOBIHOC
2009
ACM
14 years 10 months ago
Admission control and scheduling for QoS guarantees for variable-bit-rate applications on wireless channels
Providing differentiated Quality of Service (QoS) over unreliable wireless channels is an important challenge for supporting several future applications. We analyze a model that h...
I-Hong Hou, P. R. Kumar