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» On Kernel Methods for Relational Learning
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SDM
2008
SIAM
134views Data Mining» more  SDM 2008»
13 years 9 months ago
Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...
ACL
2006
13 years 9 months ago
Chinese-English Term Translation Mining Based on Semantic Prediction
Using abundant Web resources to mine Chinese term translations can be applied in many fields such as reading/writing assistant, machine translation and crosslanguage information r...
Gaolin Fang, Hao Yu, Fumihito Nishino
NIPS
2004
13 years 9 months ago
Identifying Protein-Protein Interaction Sites on a Genome-Wide Scale
Protein interactions typically arise from a physical interaction of one or more small sites on the surface of the two proteins. Identifying these sites is very important for drug ...
Haidong Wang, Eran Segal, Asa Ben-Hur, Daphne Koll...
NN
2006
Springer
13 years 7 months ago
Self-organizing neural networks to support the discovery of DNA-binding motifs
Identification of the short DNA sequence motifs that serve as binding targets for transcription factors is an important challenge in bioinformatics. Unsupervised techniques from t...
Shaun Mahony, Panayiotis V. Benos, Terry J. Smith,...
IMC
2010
ACM
13 years 5 months ago
Temporally oblivious anomaly detection on large networks using functional peers
Previous methods of network anomaly detection have focused on defining a temporal model of what is "normal," and flagging the "abnormal" activity that does not...
Kevin M. Carter, Richard Lippmann, Stephen W. Boye...