55 search results - page 6 / 11 » Supervised Learning by Training on Aggregate Outputs |
DELTA
2008
IEEE
13 years 10 months ago
2008
IEEE
We propose a bio-inspired signal processing method for odor discrimination. A spiking neural network is trained with a supervised learning rule so as to classify the analog outputs...
ICTAI
2009
IEEE
14 years 3 months ago
2009
IEEE
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
NIPS
2007
13 years 10 months ago
2007
We propose a compact, low power VLSI network of spiking neurons which can learn to classify complex patterns of mean firing rates on–line and in real–time. The network of int...
BMCBI
2010
13 years 8 months ago
2010
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
NN
2008
Springer
13 years 8 months ago
2008
Springer
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...