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SIGIR
2006
ACM
16 years 16 days 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 6 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 5 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 5 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 4 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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