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COLT
2005
Springer
15 years 12 months ago
Generalization Error Bounds Using Unlabeled Data
We present two new methods for obtaining generalization error bounds in a semi-supervised setting. Both methods are based on approximating the disagreement probability of pairs of ...
Matti Kääriäinen
WSDM
2012
ACM
309views Data Mining» more  WSDM 2012»
14 years 2 months ago
Mining contrastive opinions on political texts using cross-perspective topic model
This paper presents a novel opinion mining research problem, which is called Contrastive Opinion Modeling (COM). Given any query topic and a set of text collections from multiple ...
Yi Fang, Luo Si, Naveen Somasundaram, Zhengtao Yu
KDD
2008
ACM
244views Data Mining» more  KDD 2008»
16 years 6 months ago
Probabilistic latent semantic visualization: topic model for visualizing documents
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
ICML
2006
IEEE
16 years 7 months ago
Constructing informative priors using transfer learning
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
Rajat Raina, Andrew Y. Ng, Daphne Koller

Publication
170views
15 years 5 months ago
Covariance Regularization for Supervised Learning in High Dimensions
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
Daniel L. Elliott, Charles W. Anderson, Michael Ki...