Sciweavers

200 search results - page 4 / 40
» Margin based Active Learning for LVQ Networks
Sort
View
CORR
2010
Springer
163views Education» more  CORR 2010»
13 years 5 months ago
Faster Rates for training Max-Margin Markov Networks
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
ICONIP
2008
13 years 9 months ago
A Novel Approach for Hardware Based Sound Classification
Several applications would emerge from the development of efficient and robust sound classification systems able to identify the nature of non-speech sound sources. This paper prop...
Mauricio Kugler, Victor Alberto Parcianello Benso,...
FGCN
2008
IEEE
155views Communications» more  FGCN 2008»
13 years 9 months ago
Modeling the Marginal Distribution of Gene Expression with Mixture Models
We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
Edward Wijaya, Hajime Harada, Paul Horton
ESANN
2007
13 years 9 months ago
A supervised learning approach based on STDP and polychronization in spiking neuron networks
We propose a network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, biol...
Hélène Paugam-Moisy, Régis Ma...
NIPS
2003
13 years 9 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller