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102
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KDD
2008
ACM
259views Data Mining» more  KDD 2008»
15 years 11 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
BMCBI
2007
136views more  BMCBI 2007»
14 years 11 months ago
Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees
Background: In vertebrates, a large part of gene transcriptional regulation is operated by cisregulatory modules. These modules are believed to be regulating much of the tissue-sp...
Xiaoyu Chen, Mathieu Blanchette
81
Voted
CIKM
2004
Springer
15 years 4 months ago
The robustness of content-based search in hierarchical peer to peer networks
Hierarchical peer to peer networks with multiple directory services are an important architecture for large-scale file sharing due to their effectiveness and efficiency. Recent ...
M. Elena Renda, Jamie Callan
NIPS
2004
15 years 8 days ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
NIPS
2003
15 years 8 days ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
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