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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
15 years 10 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
ICNSC
2007
IEEE
15 years 4 months ago
Associative Memory for Noisy and Structurally Deformed Two-Dimensional Images Using Neural Networks
—This paper studies the problem of understanding noisy and structurally deformed two-dimensional images by means of abstractly defined neural works. First, in the framework of sy...
Hiroshi Inaba, Tomoki Takahashi, Keylan Alimhan
IJCNN
2000
IEEE
15 years 2 months ago
An Incremental Growing Neural Network and its Application to Robot Control
This paper describes a novel network model, which is able to control its growth on the basis of the approximation requests. Two classes of self-tuning neural models are considered...
A. Carlevarino, R. Martinotti, Giorgio Metta, Giul...
ICML
1991
IEEE
15 years 1 months ago
Constructive Induction in Knowledge-Based Neural Networks
Artificial neural networks have proven to be a successful, general method for inductive learning from examples. However, they have not often been viewed in terms of constructive ...
Geoffrey G. Towell, Mark Craven, Jude W. Shavlik
NCA
2011
IEEE
14 years 5 months ago
Privacy preserving Back-propagation neural network learning over arbitrarily partitioned data
—Neural Networks have been an active research area for decades. However, privacy bothers many when the training dataset for the neural networks is distributed between two parties...
Ankur Bansal, Tingting Chen, Sheng Zhong