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DELTA
2008
IEEE
15 years 6 months ago
A Spiking Neural Network for Gas Discrimination Using a Tin Oxide Sensor Array
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...
Maxime Ambard, Bin Guo, Dominique Martinez, Amine ...
153
Voted
ML
2000
ACM
124views Machine Learning» more  ML 2000»
15 years 4 months ago
Text Classification from Labeled and Unlabeled Documents using EM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
134
Voted
JMLR
2010
154views more  JMLR 2010»
14 years 11 months ago
MOA: Massive Online Analysis
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collecti...
Albert Bifet, Geoff Holmes, Richard Kirkby, Bernha...
116
Voted
CVPR
2008
IEEE
16 years 6 months ago
Multiple-instance ranking: Learning to rank images for image retrieval
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
Yang Hu, Mingjing Li, Nenghai Yu
ICML
2003
IEEE
16 years 5 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty