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» Regularized Learning with Networks of Features
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VLSISP
2002
112views more  VLSISP 2002»
14 years 11 months ago
Minimizing Buffer Requirements under Rate-Optimal Schedule in Regular Dataflow Networks
Large-grain synchronous dataflow graphs or multi-rate graphs have the distinct feature that the nodes of the dataflow graph fire at different rates. Such multi-rate large-grain dat...
Ramaswamy Govindarajan, Guang R. Gao, Palash Desai
JMLR
2012
13 years 2 months ago
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
Marco Grzegorczyk, Dirk Husmeier
PKDD
2010
Springer
178views Data Mining» more  PKDD 2010»
14 years 9 months ago
Graph Regularized Transductive Classification on Heterogeneous Information Networks
A heterogeneous information network is a network composed of multiple types of objects and links. Recently, it has been recognized that strongly-typed heterogeneous information net...
Ming Ji, Yizhou Sun, Marina Danilevsky, Jiawei Han...
CORR
2011
Springer
200views Education» more  CORR 2011»
14 years 6 months ago
Using Feature Weights to Improve Performance of Neural Networks
Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant fe...
Ridwan Al Iqbal
CVPR
2011
IEEE
14 years 7 months ago
Sharing Features Between Objects and Their Attributes
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
Sung Ju Hwang, Fei Sha, Kristen Grauman