Sciweavers

1456 search results - page 263 / 292
» Two Techniques to Improve Finite Model Search
Sort
View
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
SPEECH
2010
142views more  SPEECH 2010»
13 years 6 months ago
Analysis of statistical parametric and unit selection speech synthesis systems applied to emotional speech
We have applied two state-of-the-art speech synthesis techniques (unit selection and HMM-based synthesis) to the synthesis of emotional speech. A series of carefully designed perc...
Roberto Barra-Chicote, Junichi Yamagishi, Simon Ki...
SC
2009
ACM
14 years 2 months ago
Enabling high-fidelity neutron transport simulations on petascale architectures
The UNIC code is being developed as part of the DOE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. UNIC is an unstructured, deterministic neutron transport c...
Dinesh K. Kaushik, Micheal Smith, Allan Wollaber, ...
CVPR
2003
IEEE
14 years 9 months ago
Learning Bayesian Network Classifiers for Facial Expression Recognition using both Labeled and Unlabeled Data
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...
KDD
2009
ACM
232views Data Mining» more  KDD 2009»
14 years 10 days ago
Probabilistic latent semantic user segmentation for behavioral targeted advertising
Behavioral Targeting (BT), which aims to deliver the most appropriate advertisements to the most appropriate users, is attracting much attention in online advertising market. A ke...
Xiaohui Wu, Jun Yan, Ning Liu, Shuicheng Yan, Ying...