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ICML
2010
IEEE
15 years 7 months ago
Online Streaming Feature Selection
We study an interesting and challenging problem, online streaming feature selection, in which the size of the feature set is unknown, and not all features are available for learni...
Xindong Wu, Kui Yu, Hao Wang, Wei Ding
CVPR
2010
IEEE
15 years 11 months 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...
ICML
2003
IEEE
16 years 7 months ago
Testing Exchangeability On-Line
The majority of theoretical work in machine learning is done under the assumption of exchangeability: essentially, it is assumed that the examples are generated from the same prob...
Vladimir Vovk, Ilia Nouretdinov, Alexander Gammerm...
ECTEL
2007
Springer
16 years 20 days ago
Using MotSaRT to Support On-Line Teachers in Student Motivation
Motivation to learn is affected by a student’s self-efficacy, goal orientation, locus of control and perceived task difficulty. In the classroom, teachers know how to motivate th...
Teresa Hurley, Stephan Weibelzahl
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
15 years 6 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay