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COMBINATORICS
2006
129views more  COMBINATORICS 2006»
13 years 10 months ago
Descendants in Increasing Trees
Simple families of increasing trees can be constructed from simply generated tree families, if one considers for every tree of size n all its increasing labellings, i. e. labellin...
Markus Kuba, Alois Panholzer
SIGIR
2008
ACM
13 years 10 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
CORR
2010
Springer
92views Education» more  CORR 2010»
13 years 11 months ago
Hardness Results for Agnostically Learning Low-Degree Polynomial Threshold Functions
Hardness results for maximum agreement problems have close connections to hardness results for proper learning in computational learning theory. In this paper we prove two hardnes...
Ilias Diakonikolas, Ryan O'Donnell, Rocco A. Serve...
CVPR
2011
IEEE
13 years 2 months ago
A Hierarchical Conditional Random Field Model for Labeling and Segmenting Images of Street Scenes
Simultaneously segmenting and labeling images is a fundamental problem in Computer Vision. In this paper, we introduce a hierarchical CRF model to deal with the problem of labelin...
Qixing Huang, Mei Han, Bo Wu, Sergey Ioffe
CEAS
2007
Springer
14 years 2 months ago
Online Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
D. Sculley