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» Co-Tracking Using Semi-Supervised Support Vector Machines
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JMLR
2010
185views more  JMLR 2010»
15 years 1 months ago
Multiple Kernel Learning on the Limit Order Book
Simple features constructed from order book data for the EURUSD currency pair were used to construct a set of kernels. These kernels were used both individually and simultaneously...
Tristan Fletcher, Zakria Hussain, John Shawe-Taylo...
ICIP
2008
IEEE
16 years 8 months ago
Emotional valence categorization using holistic image features
Can a machine learn to perceive emotions as evoked by an artwork? Here we propose an emotion categorization system, trained by ground truth from psychology studies. The training d...
Victoria Yanulevskaya, Jan van Gemert, Katharina R...
ICASSP
2009
IEEE
15 years 4 months ago
Target detection using incremental learning on single-trial evoked response
The human neural responses associated with cognitive events, referred as event related potentials (ERPs), can provide reliable inference for target image detection. Incremental le...
Yonghong Huang, Deniz Erdogmus, Misha Pavel, Kenne...
TIFS
2008
149views more  TIFS 2008»
15 years 6 months ago
Using One-Class SVMs and Wavelets for Audio Surveillance
This paper presents a procedure aimed at recognizing environmental sounds for surveillance and security applications. We propose to apply One-Class Support Vector Machines (1-SVMs...
Asma Rabaoui, Manuel Davy, Stéphane Rossign...
COLING
2008
15 years 7 months ago
A Hybrid Generative/Discriminative Framework to Train a Semantic Parser from an Un-annotated Corpus
We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HMSV...
Deyu Zhou, Yulan He