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COLT
1993
Springer
15 years 1 months ago
Learning Binary Relations Using Weighted Majority Voting
In this paper we demonstrate how weighted majority voting with multiplicative weight updating can be applied to obtain robust algorithms for learning binary relations. We first pre...
Sally A. Goldman, Manfred K. Warmuth
ICML
2003
IEEE
15 years 10 months ago
Identifying Predictive Structures in Relational Data Using Multiple Instance Learning
This paper introduces an approach for identifying predictive structures in relational data using the multiple-instance framework. By a predictive structure, we mean a structure th...
Amy McGovern, David Jensen
ML
2000
ACM
103views Machine Learning» more  ML 2000»
14 years 9 months ago
Phase Transitions in Relational Learning
One of the major limitations of relational learning is due to the complexity of verifying hypotheses on examples. In this paper we investigate this task in light of recent publishe...
Attilio Giordana, Lorenza Saitta
JMLR
2012
13 years 4 days ago
A metric learning perspective of SVM: on the relation of LMNN and SVM
Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor algorithm, LMNN, are two very popular learning algorithms with quite different learning biases. In this paper...
Huyen Do, Alexandros Kalousis, Jun Wang, Adam Wozn...
EURODAC
1995
IEEE
126views VHDL» more  EURODAC 1995»
15 years 1 months ago
Use of embedded scheduling to compile VHDL for effective parallel simulation
This paper describes VHDL compilation techniques, embodied in the Auriga compiler [3,14], which facilitate parallel or distributed simulation by embedding evaluation scheduling in...
John Willis, Zhiyuan Li, Tsang-Puu Lin