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157
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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 4 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
154
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ECCV
2010
Springer
15 years 6 months ago
Optimum Subspace Learning and Error Correction for Tensors
Confronted with the high-dimensional tensor-like visual data, we derive a method for the decomposition of an observed tensor into a low-dimensional structure plus unbounded but spa...
124
Voted
JMLR
2010
101views more  JMLR 2010»
14 years 10 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
ICDM
2007
IEEE
143views Data Mining» more  ICDM 2007»
15 years 10 months ago
Bit Sequences and Biclustering of Text Documents
We propose a new technique for clustering of text documents that relies on a biclustering structure constructed on terms and documents. Our approach makes use of a greedy algorith...
Selim Mimaroglu, Kuniaki Uehara
160
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ICCV
2009
IEEE
16 years 8 months ago
A Probabilistic Framework for Partial Intrinsic Symmetries in Geometric Data
In this paper, we present a novel algorithm for partial intrinsic symmetry detection in 3D geometry. Unlike previous work, our algorithm is based on a conceptually simple and st...
Ruxandra Lasowski, Art Tevs, Hans-Peter Seidel, Mi...