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» Algorithms for Large, Sparse Network Alignment Problems
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KCAP
2003
ACM
15 years 7 months ago
Using transformations to improve semantic matching
Many AI tasks require determining whether two knowledge representations encode the same knowledge. Solving this matching problem is hard because representations may encode the sam...
Peter Z. Yeh, Bruce W. Porter, Ken Barker
ICDM
2007
IEEE
151views Data Mining» more  ICDM 2007»
15 years 6 months ago
Combining Collective Classification and Link Prediction
The problems of object classification (labeling the nodes of a graph) and link prediction (predicting the links in a graph) have been largely studied independently. Commonly, obje...
Mustafa Bilgic, Galileo Namata, Lise Getoor
IJCNN
2007
IEEE
15 years 8 months ago
Two-stage Multi-class AdaBoost for Facial Expression Recognition
— Although AdaBoost has achieved great success, it still suffers from following problems: (1) the training process could be unmanageable when the number of features is extremely ...
Hongbo Deng, Jianke Zhu, Michael R. Lyu, Irwin Kin...
NGC
2001
Springer
157views Communications» more  NGC 2001»
15 years 6 months ago
Aggregated Multicast with Inter-Group Tree Sharing
IP multicast suffers from scalability problems for large numbers of multicast groups, since each router keeps forwarding state proportional to the number of multicast tree passing ...
Aiguo Fei, Jun-Hong Cui, Mario Gerla, Michalis Fal...
ATAL
2005
Springer
15 years 8 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson