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134
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KDD
2010
ACM
245views Data Mining» more  KDD 2010»
15 years 4 months ago
Learning incoherent sparse and low-rank patterns from multiple tasks
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Jianhui Chen, Ji Liu, Jieping Ye
133
Voted
JMLR
2008
150views more  JMLR 2008»
15 years 2 months ago
Discriminative Learning of Max-Sum Classifiers
The max-sum classifier predicts n-tuple of labels from n-tuple of observable variables by maximizing a sum of quality functions defined over neighbouring pairs of labels and obser...
Vojtech Franc, Bogdan Savchynskyy
MIR
2010
ACM
207views Multimedia» more  MIR 2010»
15 years 1 months ago
Learning to rank for content-based image retrieval
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...
ICML
1996
IEEE
16 years 3 months ago
On the Learnability of the Uncomputable
Within Valiant'smodel of learning as formalized by Kearns, we show that computable total predicates for two formallyuncomputable problems the classical Halting Problem, and t...
Richard H. Lathrop
133
Voted
UIC
2007
Springer
15 years 8 months ago
Ontology-Based Semantic Recommendation for Context-Aware E-Learning
Nowadays, e-learning systems are widely used for education and training in universities and companies because of their electronic course content access and virtual classroom partic...
Zhiwen Yu, Yuichi Nakamura, Seiie Jang, Shoji Kaji...