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ICML
2010
IEEE
13 years 8 months ago
A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices
We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact fac...
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, His...
JMLR
2012
11 years 10 months ago
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models
This paper studies issues relating to the parameterization of probability distributions over binary data sets. Several such parameterizations of models for binary data are known, ...
David Buchman, Mark W. Schmidt, Shakir Mohamed, Da...
CIKM
2011
Springer
12 years 7 months ago
Semi-supervised multi-task learning of structured prediction models for web information extraction
Extracting information from web pages is an important problem; it has several applications such as providing improved search results and construction of databases to serve user qu...
Paramveer S. Dhillon, Sundararajan Sellamanickam, ...
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 8 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
CVPR
2001
IEEE
14 years 9 months ago
Diffusion Tensor Regularization with Constraints Preservation
This paper deals with the problem of regularizing noisy fields of diffusion tensors, considered as symmetric and semi-positive definite ? ? ? matrices (as for instance 2D structur...
David Tschumperlé, Rachid Deriche