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» Multi-Label Learning with Weak Label
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CVPR
2012
IEEE
11 years 10 months ago
Weak attributes for large-scale image retrieval
Attribute-based query offers an intuitive way of image retrieval, in which users can describe the intended search targets with understandable attributes. In this paper, we develop...
Felix X. Yu, Rongrong Ji, Ming-Hen Tsai, Guangnan ...
AAAI
2007
13 years 9 months ago
Semi-Supervised Learning with Very Few Labeled Training Examples
In semi-supervised learning, a number of labeled examples are usually required for training an initial weakly useful predictor which is in turn used for exploiting the unlabeled e...
Zhi-Hua Zhou, De-Chuan Zhan, Qiang Yang
IJCAI
2003
13 years 8 months ago
Active Learning with Strong and Weak Views: A Case Study on Wrapper Induction
Multi-view learners reduce the need for labeled data by exploiting disjoint sub-sets of features (views), each of which is sufficient for learning. Such algorithms assume that eac...
Ion Muslea, Steven Minton, Craig A. Knoblock
ICMLA
2010
13 years 5 months ago
Boosting Multi-Task Weak Learners with Applications to Textual and Social Data
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
CVPR
2010
IEEE
14 years 20 days ago
Visual Tracking via Weakly Supervised Learning from Multiple Imperfect Oracles
Long-term persistent tracking in ever-changing environments is a challenging task, which often requires addressing difficult object appearance update problems. To solve them, most...
Bineng Zhong, Hongxun Yao, Sheng Chen, Xiaotong Yu...