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JMLR
2008
117views more  JMLR 2008»
9 years 7 months ago
Closed Sets for Labeled Data
Closed sets have been proven successful in the context of compacted data representation for association rule learning. However, their use is mainly descriptive, dealing only with ...
Gemma C. Garriga, Petra Kralj, Nada Lavrac
CORR
2006
Springer
105views Education» more  CORR 2006»
9 years 7 months ago
Generalization error bounds in semi-supervised classification under the cluster assumption
We consider semi-supervised classification when part of the available data is unlabeled. These unlabeled data can be useful for the classification problem when we make an assumpti...
Philippe Rigollet
SIGIR
2010
ACM
9 years 7 months ago
SED: supervised experimental design and its application to text classification
In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit ...
Yi Zhen, Dit-Yan Yeung
DAGM
2010
Springer
9 years 8 months ago
On-Line Multi-view Forests for Tracking
Abstract. A successful approach to tracking is to on-line learn discriminative classifiers for the target objects. Although these trackingby-detection approaches are usually fast a...
Christian Leistner, Martin Godec, Amir Saffari, Ho...
AAAI
1998
9 years 8 months ago
Learning to Classify Text from Labeled and Unlabeled Documents
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
NIPS
2003
9 years 8 months ago
Learning with Local and Global Consistency
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal,...
IJCAI
2003
9 years 8 months ago
SVMC: Single-Class Classification With Support Vector Machines
Single-Class Classification (SCC) seeks to distinguish one class of data from the universal set of multiple classes. We present a new SCC algorithm that efficiently computes an ac...
Hwanjo Yu
IJCAI
2003
9 years 8 months ago
Semi-Supervised Learning with Explicit Misclassification Modeling
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Massih-Reza Amini, Patrick Gallinari
NIPS
2001
9 years 8 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
NAACL
2001
9 years 8 months ago
Unsupervised Learning of Name Structure From Coreference Data
We present two methods for learning the structure of personal names from unlabeled data. The first simply uses a few implicit constraints governing this structure to gain a toehol...
Eugene Charniak
books