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» On a theory of learning with similarity functions
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TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
IJCNN
2006
IEEE
14 years 1 months ago
An optimization approach to achieve unsupervised segmentation and binding in a dynamical network
— We present a novel network of oscillatory units, whose behavior is described by the amplitude and phase of oscillations. While building on previous work, the system presented i...
A. Ravishankar Rao, Guillermo A. Cecchi, Charles C...
CVPR
2009
IEEE
15 years 2 months ago
A Revisit of Generative Model for Automatic Image Annotation using Markov Random Fields
Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many we...
Yu Xiang (Fudan University), Xiangdong Zhou (Fudan...
NIPS
2000
13 years 9 months ago
One Microphone Source Separation
Source separation, or computational auditory scene analysis, attempts to extract individual acoustic objects from input which contains a mixture of sounds from different sources, ...
Sam T. Roweis
DIGRA
2005
Springer
14 years 1 months ago
The Nip and the Bite
An examination of the contributions that can be made by the field of non-mechanistic cybernetics (as elaborated by Gregory Bateson and Anthony Wilden) to a theory of videogames th...
Darshana Jayemanne