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KDD
2012
ACM
247views Data Mining» more  KDD 2012»
11 years 10 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
ICML
2003
IEEE
14 years 8 months ago
Learning with Knowledge from Multiple Experts
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers...
Matthew Richardson, Pedro Domingos
COOPIS
2003
IEEE
14 years 1 months ago
Learning to Invoke Web Forms
Emerging Web standards promise a network of heterogeneous yet interoperable Web Services. Web Services would greatly simplify the development of many kinds of information agents a...
Nicholas Kushmerick
NECO
2002
104views more  NECO 2002»
13 years 7 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
ICCV
2007
IEEE
14 years 9 months ago
Supervised Learning of Image Restoration with Convolutional Networks
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...