Sciweavers

963 search results - page 5 / 193
» Active Learning by Labeling Features
Sort
View
JAIR
2006
105views more  JAIR 2006»
13 years 8 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
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 6 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
IJCAI
2007
13 years 10 months ago
Common Sense Based Joint Training of Human Activity Recognizers
Given sensors to detect object use, commonsense priors of object usage in activities can reduce the need for labeled data in learning activity models. It is often useful, however,...
Shiaokai Wang, William Pentney, Ana-Maria Popescu,...
ICML
2004
IEEE
14 years 2 months ago
Active learning of label ranking functions
The effort necessary to construct labeled sets of examples in a supervised learning scenario is often disregarded, though in many applications, it is a time-consuming and expensi...
Klaus Brinker
AAAI
2006
13 years 10 months ago
Active Learning with Near Misses
Assume that we are trying to build a visual recognizer for a particular class of objects--chairs, for example--using existing induction methods. Assume the assistance of a human t...
Nela Gurevich, Shaul Markovitch, Ehud Rivlin