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» Learning from General Label Constraints
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COLT
2001
Springer
15 years 2 months ago
Ultraconservative Online Algorithms for Multiclass Problems
In this paper we study a paradigm to generalize online classification algorithms for binary classification problems to multiclass problems. The particular hypotheses we investig...
Koby Crammer, Yoram Singer
WWW
2008
ACM
15 years 10 months ago
Learning to classify short and sparse text & web with hidden topics from large-scale data collections
This paper presents a general framework for building classifiers that deal with short and sparse text & Web segments by making the most of hidden topics discovered from larges...
Xuan Hieu Phan, Minh Le Nguyen, Susumu Horiguchi
CVPR
2006
IEEE
15 years 11 months ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
SDM
2009
SIAM
394views Data Mining» more  SDM 2009»
15 years 6 months ago
Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence.
Many real-world applications call for learning predictive relationships from multi-modal data. In particular, in multi-media and web applications, given a dataset of images and th...
Oksana Yakhnenko, Vasant Honavar
NIPS
2003
14 years 11 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Stuart Andrews, Thomas Hofmann