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» The Inefficiency of Batch Training for Large Training Sets
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ICDM
2007
IEEE
157views Data Mining» more  ICDM 2007»
13 years 9 months ago
Training Conditional Random Fields by Periodic Step Size Adaptation for Large-Scale Text Mining
For applications with consecutive incoming training examples, on-line learning has the potential to achieve a likelihood as high as off-line learning without scanning all availabl...
Han-Shen Huang, Yu-Ming Chang, Chun-Nan Hsu
ATMOS
2010
150views Optimization» more  ATMOS 2010»
13 years 6 months ago
Dynamic Graph Generation and Dynamic Rolling Horizon Techniques in Large Scale Train Timetabling
The aim of the train timetabling problem is to find a conflict free timetable for a set of passenger and freight trains along their routes in an infrastructure network. Several ...
Frank Fischer, Christoph Helmberg
ECML
2007
Springer
14 years 1 months ago
Learning to Classify Documents with Only a Small Positive Training Set
Many real-world classification applications fall into the class of positive and unlabeled (PU) learning problems. In many such applications, not only could the negative training ex...
Xiaoli Li, Bing Liu, See-Kiong Ng
FGR
2008
IEEE
299views Biometrics» more  FGR 2008»
14 years 2 months ago
Face recognition with occlusions in the training and testing sets
Partial occlusions in face images pose a great problem for most face recognition algorithms. Several solutions to this problem have been proposed over the years – ranging from d...
Hongjun Jia, Aleix M. Martínez
CVPR
2008
IEEE
14 years 2 months ago
Learning a geometry integrated image appearance manifold from a small training set
While low-dimensional image representations have been very popular in computer vision, they suffer from two limitations: (i) they require collecting a large and varied training se...
Yilei Xu, Amit K. Roy Chowdhury