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COLT
2008
Springer
15 years 6 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál
AAAI
2010
15 years 6 months ago
Multi-Label Learning with Weak Label
Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
Yu-Yin Sun, Yin Zhang, Zhi-Hua Zhou
NIPS
2004
15 years 6 months ago
The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees
Prediction suffix trees (PST) provide a popular and effective tool for tasks such as compression, classification, and language modeling. In this paper we take a decision theoretic...
Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
FOCM
2006
97views more  FOCM 2006»
15 years 4 months ago
Learning Rates of Least-Square Regularized Regression
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
Qiang Wu, Yiming Ying, Ding-Xuan Zhou
PCM
2010
Springer
183views Multimedia» more  PCM 2010»
15 years 3 months ago
Fast H.264 Encoding Based on Statistical Learning
Abstract. In this paper, we propose an efficient video coding system that applies statistical learning methods to reduce the computational cost in H.264 encoder. The proposed metho...
Chen-Kuo Chiang, Shang-Hong Lai