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ECCV
2008
Springer
16 years 1 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
SASO
2010
IEEE
14 years 9 months ago
Extracting Overlay Invariants of Distributed Systems for Autonomic System Management
Many large-scale distributed systems have been built with great complexity to run Internet services. Due to the heterogeneity and dynamics of complex systems, it is very difficult ...
Hanhuai Shan, Guofei Jiang, Kenji Yoshihira
AAAI
1998
15 years 1 months ago
Learning to Extract Symbolic Knowledge from the World Wide Web
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a...
Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew M...
SEMWEB
2009
Springer
15 years 4 months ago
Extracting Enterprise Vocabularies Using Linked Open Data
A common vocabulary is vital to smooth business operation, yet codifying and maintaining an enterprise vocabulary is an arduous, manual task. We describe a process to automatically...
Julian Dolby, Achille Fokoue, Aditya Kalyanpur, Ed...
CIKM
2009
Springer
15 years 6 months ago
Combining labeled and unlabeled data with word-class distribution learning
We describe a novel simple and highly scalable semi-supervised method called Word-Class Distribution Learning (WCDL), and apply it the task of information extraction (IE) by utili...
Yanjun Qi, Ronan Collobert, Pavel Kuksa, Koray Kav...