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» MILIS: Multiple Instance Learning with Instance Selection
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LREC
2010
176views Education» more  LREC 2010»
13 years 9 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
CVPR
2011
IEEE
13 years 5 months ago
Dynamic Batch Mode Active Learning
Active learning techniques have gained popularity in reducing human effort to annotate data instances for inducing a classifier. When faced with large quantities of unlabeled dat...
Shayok Chakraborty, Vineeth Balasubramanian, Sethu...
CVPR
2010
IEEE
14 years 4 months ago
Far-Sighted Active Learning on a Budget for Image and Video Recognition
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Sudheendra Vijayanarasimhan, Prateek Jain, Kristen...
ICML
2010
IEEE
13 years 8 months ago
Active Learning for Multi-Task Adaptive Filtering
In this paper, we propose an Active Learning (AL) framework for the Multi-Task Adaptive Filtering (MTAF) problem. Specifically, we explore AL approaches to rapidly improve an MTAF...
Abhay Harpale, Yiming Yang
AIMSA
2008
Springer
14 years 2 months ago
Prototypes Based Relational Learning
Relational instance-based learning (RIBL) algorithms offer high prediction capabilities. However, they do not scale up well, specially in domains where there is a time bound for c...
Rocío García-Durán, Fernando ...