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PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
13 years 8 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
JAIR
2006
105views more  JAIR 2006»
13 years 10 months ago
Active Learning with Multiple Views
Active learners alleviate the burden of labeling large amounts of data by detecting and asking the user to label only the most informative examples in the domain. We focus here on...
Ion Muslea, Steven Minton, Craig A. Knoblock
ECML
2003
Springer
14 years 3 months ago
Learning Context Free Grammars in the Limit Aided by the Sample Distribution
We present an algorithm for learning context free grammars from positive structural examples (unlabeled parse trees). The algorithm receives a parameter in the form of a finite se...
Yoav Seginer
ICCV
2011
IEEE
12 years 10 months ago
Learning Spatiotemporal Graphs of Human Activities
Complex human activities occurring in videos can be defined in terms of temporal configurations of primitive actions. Prior work typically hand-picks the primitives, their total...
William Brendel, Sinisa Todorovic
ICML
2000
IEEE
14 years 11 months ago
Meta-Learning by Landmarking Various Learning Algorithms
Landmarking is a novel approach to describing tasks in meta-learning. Previous approaches to meta-learning mostly considered only statistics-inspired measures of the data as a sou...
Bernhard Pfahringer, Hilan Bensusan, Christophe G....