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CVPR
2012
IEEE
13 years 3 days ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu
ECAI
2008
Springer
14 years 11 months ago
MTForest: Ensemble Decision Trees based on Multi-Task Learning
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
Qing Wang, Liang Zhang, Mingmin Chi, Jiankui Guo
75
Voted
LREC
2010
176views Education» more  LREC 2010»
14 years 11 months ago
There's no Data like More Data? Revisiting the Impact of Data Size on a Classification Task
In the paper we investigate the impact of data size on a Word Sense Disambiguation task (WSD). We question the assumption that the knowledge acquisition bottleneck, which is known...
Ines Rehbein, Josef Ruppenhofer
ICIAP
1999
ACM
15 years 1 months ago
Learning Visual Operators from Examples: A New Paradigm in Image Processing
This paper presents a general strategy for designing efficient visual operators. The approach is highly task oriented and what constitutes the relevant information is defined by...
Hans Knutsson, Magnus Borga
IJCAI
2003
14 years 11 months ago
Does a New Simple Gaussian Weighting Approach Perform Well in Text Categorization?
A new approach to the Text Categorization problem is here presented. It is called Gaussian Weighting and it is a supervised learning algorithm that, during the training phase, est...
Giorgio Maria Di Nunzio, Alessandro Micarelli