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» On Kernel Methods for Relational Learning
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163
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AAAI
2012
13 years 5 months ago
Ontological Smoothing for Relation Extraction with Minimal Supervision
Relation extraction, the process of converting natural language text into structured knowledge, is increasingly important. Most successful techniques use supervised machine learni...
Congle Zhang, Raphael Hoffmann, Daniel S. Weld
ICML
2004
IEEE
16 years 4 months ago
Relational sequential inference with reliable observations
We present a trainable sequential-inference technique for processes with large state and observation spaces and relational structure. Our method assumes "reliable observation...
Alan Fern, Robert Givan
ILP
1999
Springer
15 years 7 months ago
Probabilistic Relational Models
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Daphne Koller
119
Voted
ESANN
2003
15 years 4 months ago
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Fo...
RSFDGRC
2005
Springer
156views Data Mining» more  RSFDGRC 2005»
15 years 8 months ago
Intrusion Detection System Based on Multi-class SVM
In this paper, we propose a new intrusion detection model, which keeps advantages of existing misuse detection model and anomaly detection model and resolves their problems. This ...
Hansung Lee, Jiyoung Song, Daihee Park