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» Machine-Learning Applications of Algorithmic Randomness
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ICML
2009
IEEE
14 years 10 months ago
Learning with structured sparsity
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas
ICML
2007
IEEE
14 years 10 months ago
Learning to compress images and videos
We present an intuitive scheme for lossy color-image compression: Use the color information from a few representative pixels to learn a model which predicts color on the rest of t...
Li Cheng, S. V. N. Vishwanathan
ICML
2006
IEEE
14 years 10 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
ICML
2005
IEEE
14 years 10 months ago
Computational aspects of Bayesian partition models
The conditional distribution of a discrete variable y, given another discrete variable x, is often specified by assigning one multinomial distribution to each state of x. The cost...
Mikko Koivisto, Kismat Sood
WWW
2008
ACM
14 years 10 months ago
Efficiently finding web services using a clustering semantic approach
Efficiently finding Web services on the Web is a challenging issue in service-oriented computing. Currently, UDDI is a standard for publishing and discovery of Web services, and U...
Jiangang Ma, Yanchun Zhang, Jing He