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» Adaptive Informative Sampling for Active Learning
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COLT
2007
Springer
14 years 1 months ago
Minimax Bounds for Active Learning
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
Rui Castro, Robert D. Nowak
ECTEL
2007
Springer
14 years 1 months ago
From Informal Learner to Active Content Provider: SLEAM Approach
Creation of the reusable learning content in the process of work is a challenging but promising trend in e-learning and knowledge management. While the main research focus nowadays...
Oleg Rostanin, Markus Ludwar
ECML
2007
Springer
14 years 1 months ago
Dual Strategy Active Learning
Abstract. Active Learning methods rely on static strategies for sampling unlabeled point(s). These strategies range from uncertainty sampling and density estimation to multi-factor...
Pinar Donmez, Jaime G. Carbonell, Paul N. Bennett
COLT
2010
Springer
13 years 5 months ago
Robust Selective Sampling from Single and Multiple Teachers
We present a new online learning algorithm in the selective sampling framework, where labels must be actively queried before they are revealed. We prove bounds on the regret of ou...
Ofer Dekel, Claudio Gentile, Karthik Sridharan
CVPR
2010
IEEE
14 years 29 days ago
Adaptive Generic Learning for Face Recognition from a Single Sample per Person
Real-world face recognition systems often have to face the single sample per person (SSPP) problem, that is, only a single training sample for each person is enrolled in the datab...
Yu Su, Shiguang Shan, Xilin Chen, wen Gao