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TKDE
2010
168views more  TKDE 2010»
13 years 3 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
JMLR
2010
147views more  JMLR 2010»
13 years 1 days ago
Image Denoising with Kernels Based on Natural Image Relations
A successful class of image denoising methods is based on Bayesian approaches working in wavelet representations. The performance of these methods improves when relations among th...
Valero Laparra, Juan Gutierrez, Gustavo Camps-Vall...
SSPR
2010
Springer
13 years 3 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
WWW
2008
ACM
14 years 5 months ago
Learning transportation mode from raw gps data for geographic applications on the web
Geographic information has spawned many novel Web applications where global positioning system (GPS) plays important roles in bridging the applications and end users. Learning kno...
Yu Zheng, Like Liu, Longhao Wang, Xing Xie
ISCAS
2006
IEEE
116views Hardware» more  ISCAS 2006»
13 years 11 months ago
Signal processing for brain-computer interface: enhance feature extraction and classification
Abstract-In this paper we present a new scheme for brain imaginary movement invovles sophisticated spatial-temporalsignal processing and classification for electroencephalogram spe...
Haihong Zhang, Cuntai Guan, Yuanqing Li