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» Learning Gaussian Process Models from Uncertain Data
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103
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ICML
2003
IEEE
16 years 3 months ago
On Kernel Methods for Relational Learning
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
Chad M. Cumby, Dan Roth
122
Voted
BSN
2006
IEEE
131views Sensor Networks» more  BSN 2006»
15 years 8 months ago
Elaborating Sensor Data using Temporal and Spatial Commonsense Reasoning
Ubiquitous computing has established a vision of computation where computers are so deeply integrated into our lives that they become both invisible and everywhere. In order to ha...
Bo Morgan, Push Singh
140
Voted
ICDM
2010
IEEE
273views Data Mining» more  ICDM 2010»
15 years 18 days ago
Learning Maximum Lag for Grouped Graphical Granger Models
Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
Amit Dhurandhar
BMCBI
2006
119views more  BMCBI 2006»
15 years 2 months ago
Hidden Markov Model Variants and their Application
Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...
Stephen Winters-Hilt
191
Voted
ECCV
2008
Springer
15 years 4 months ago
Multiple Instance Boost Using Graph Embedding Based Decision Stump for Pedestrian Detection
Pedestrian detection in still image should handle the large appearance and stance variations arising from the articulated structure, various clothing of human as well as viewpoints...
Junbiao Pang, Qingming Huang, Shuqiang Jiang