Sciweavers

431 search results - page 59 / 87
» Observational Learning with Modular Networks
Sort
View
NIPS
2004
14 years 11 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
IJCNN
2006
IEEE
15 years 3 months ago
Neural Network Control of Spark Ignition Engines with High EGR Levels
— Research has shown substantial reductions in the oxides of nitrogen (NOx) concentrations by using 10% to 25% exhaust gas recirculation (EGR) in spark ignition (SI) engines [1]....
Atmika Singh, Jonathan Blake Vance, Brian C. Kaul,...
ICDM
2005
IEEE
187views Data Mining» more  ICDM 2005»
15 years 3 months ago
Parallel Algorithms for Distance-Based and Density-Based Outliers
An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...
Elio Lozano, Edgar Acuña
NN
2002
Springer
208views Neural Networks» more  NN 2002»
14 years 9 months ago
A spiking neuron model: applications and learning
This paper presents a biologically-inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the mo...
Chris Christodoulou, Guido Bugmann, Trevor G. Clar...
ICMLA
2008
14 years 11 months ago
Tumor Targeting for Lung Cancer Radiotherapy Using Machine Learning Techniques
Accurate lung tumor targeting in real time plays a fundamental role in image-guide radiotherapy of lung cancers. Precise tumor targeting is required for both respiratory gating an...
Tong Lin, Laura Cervino, Xiaoli Tang, Nuno Vasconc...