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SIGIR
2006
ACM
16 years 1 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
16 years 25 days ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
EEE
2005
IEEE
16 years 25 days ago
From Education to e-Learning : A Union Catalog Service of Learning Resources
Computer-Supported Collaborative Learning (CSCL) is a new learning method that is receiving an increasing amount of attention in Taiwan. With the rapid growth in learning resource...
Pei-Xian Kuo, Jyun-Jie Yan, Jan-Ming Ho
INFOCOM
2005
IEEE
16 years 24 days ago
Mobile-assisted localization in wireless sensor networks
Abstract— The localization problem is to determine an assignment of coordinates to nodes in a wireless ad-hoc or sensor network that is consistent with measured pairwise node dis...
Nissanka B. Priyantha, Hari Balakrishnan, Erik D. ...
ITCC
2005
IEEE
16 years 24 days ago
A Framework for Key Management in Mobile Ad Hoc Networks
Background: Key management in a mobile ad hoc environment is complicated by frequently partitioning network topology. Recently proposed key management systems (KMSs) provide limit...
George C. Hadjichristofi, William Joseph Adams, Na...
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