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» New Regularized Algorithms for Transductive Learning
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SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
14 years 11 months ago
Semi-Supervised Learning Based on Semiparametric Regularization
Semi-supervised learning plays an important role in the recent literature on machine learning and data mining and the developed semisupervised learning techniques have led to many...
Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Chr...
ICMLA
2004
14 years 11 months ago
Two new regularized AdaBoost algorithms
AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...
Yijun Sun, Jian Li, William W. Hager
AAAI
2000
14 years 11 months ago
Self-Supervised Learning for Visual Tracking and Recognition of Human Hand
Due to the large variation and richness of visual inputs, statistical learning gets more and more concerned in the practice of visual processing such as visual tracking and recogn...
Ying Wu, Thomas S. Huang
ALT
2010
Springer
14 years 11 months ago
Towards General Algorithms for Grammatical Inference
Many algorithms for grammatical inference can be viewed as instances of a more general algorithm which maintains a set of primitive elements, which distributionally define sets of ...
Alexander Clark
SIAMJO
2010
127views more  SIAMJO 2010»
14 years 4 months ago
Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning
We consider a recently proposed optimization formulation of multi-task learning based on trace norm regularized least squares. While this problem may be formulated as a semidefini...
Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye