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» Learning Classifiers from Semantically Heterogeneous Data
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NN
2008
Springer
201views Neural Networks» more  NN 2008»
13 years 8 months ago
Learning representations for object classification using multi-stage optimal component analysis
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Yiming Wu, Xiuwen Liu, Washington Mio
CSB
2005
IEEE
156views Bioinformatics» more  CSB 2005»
14 years 2 months ago
A Robust Meta-classification Strategy for Cancer Diagnosis from Gene Expression Data
One of the major challenges in cancer diagnosis from microarray data is to develop robust classification models which are independent of the analysis techniques used and can combi...
Gabriela Alexe, Gyan Bhanot, Babu Venkataraghavan,...
3DPH
2009
163views Healthcare» more  3DPH 2009»
13 years 10 months ago
Discriminative Human Full-Body Pose Estimation from Wearable Inertial Sensor Data
Abstract. In this paper, a method is presented that allows reconstructing the full-body pose of a person in real-time, based on the limited input from a few wearable inertial senso...
Loren Arthur Schwarz, Diana Mateus, Nassir Navab
TFS
2008
230views more  TFS 2008»
13 years 8 months ago
SGERD: A Steady-State Genetic Algorithm for Extracting Fuzzy Classification Rules From Data
Abstract--This paper considers the automatic design of fuzzyrule-based classification systems from labeled data. The performance of classifiers and the interpretability of generate...
Eghbal G. Mansoori, Mansoor J. Zolghadri, Seraj D....
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 9 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...