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AUSDM
2006
Springer
177views Data Mining» more  AUSDM 2006»
15 years 3 months ago
On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
Tatjana Eitrich, Bruno Lang
ICML
2007
IEEE
16 years 15 days ago
On the relation between multi-instance learning and semi-supervised learning
Multi-instance learning and semi-supervised learning are different branches of machine learning. The former attempts to learn from a training set consists of labeled bags each con...
Zhi-Hua Zhou, Jun-Ming Xu
ICDM
2005
IEEE
163views Data Mining» more  ICDM 2005»
15 years 5 months ago
Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...
Thomas Takeo Osugi, Kun Deng, Stephen D. Scott
AAAI
2012
13 years 2 months ago
Relative Attributes for Enhanced Human-Machine Communication
We propose to model relative attributes1 that capture the relationships between images and objects in terms of human-nameable visual properties. For example, the models can captur...
Devi Parikh, Adriana Kovashka, Amar Parkash, Krist...
ICAISC
2004
Springer
15 years 5 months ago
Comparison of Instances Seletion Algorithms I. Algorithms Survey
Abstract. Several methods were proposed to reduce the number of instances (vectors) in the learning set. Some of them extract only bad vectors while others try to remove as many in...
Norbert Jankowski, Marek Grochowski