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ICML
2010
IEEE
15 years 7 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...
ICALT
2007
IEEE
15 years 6 months ago
Personalization of Immediate Feedback to Learning Styles
Feedback provided to a user is an important part of learning and interaction in e-learning systems. In this paper we present the results of our pilot experiment aimed to study int...
Ekaterina Vasilyeva, Mykola Pechenizkiy, Tatiana G...
JMLR
2010
169views more  JMLR 2010»
15 years 1 months ago
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
TNN
2010
205views Management» more  TNN 2010»
15 years 1 months ago
Behavior-constrained support vector machines for fMRI data analysis
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
Danmei Chen, Sheng Li, Zoe Kourtzi, Si Wu
ICML
2009
IEEE
16 years 7 months ago
Learning nonlinear dynamic models
We present a novel approach for learning nonlinear dynamic models, which leads to a new set of tools capable of solving problems that are otherwise difficult. We provide theory sh...
John Langford, Ruslan Salakhutdinov, Tong Zhang