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141
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KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 3 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, ...
155
Voted
BMCBI
2007
136views more  BMCBI 2007»
15 years 3 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
CIKM
2004
Springer
15 years 8 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
149
Voted
NIPS
2004
15 years 4 months 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
156
Voted
NIPS
2003
15 years 4 months 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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