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» Generalization Error Bounds Using Unlabeled Data
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DIALM
2003
ACM
99views Algorithms» more  DIALM 2003»
14 years 18 days ago
Spatio-temporal data reduction with deterministic error bounds
A common way of storing spatio-temporal information about mobile devices is in the form of a 3D (2D geography + time) trajectory. We argue that when cellular phones and Personal D...
Hu Cao, Ouri Wolfson, Goce Trajcevski
DAGM
2004
Springer
14 years 22 days ago
Learning from Labeled and Unlabeled Data Using Random Walks
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Dengyong Zhou, Bernhard Schölkopf
COLING
2010
13 years 2 months ago
Improving Name Origin Recognition with Context Features and Unlabelled Data
We demonstrate the use of context features, namely, names of places, and unlabelled data for the detection of personal name language of origin. While some early work used either r...
Vladimir Pervouchine, Min Zhang, Ming Liu, Haizhou...
COLT
2005
Springer
14 years 27 days ago
A PAC-Style Model for Learning from Labeled and Unlabeled Data
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...
Maria-Florina Balcan, Avrim Blum
MCS
2009
Springer
14 years 2 months ago
When Semi-supervised Learning Meets Ensemble Learning
Abstract. Semi-supervised learning and ensemble learning are two important learning paradigms. The former attempts to achieve strong generalization by exploiting unlabeled data; th...
Zhi-Hua Zhou