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JMLR
2006
169views more  JMLR 2006»
15 years 4 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
NIPS
1993
15 years 6 months ago
Analyzing Cross-Connected Networks
The non-linear complexities of neural networks make network solutions difficult to understand. Sanger's contribution analysis is here extended to the analysis of networks aut...
Thomas R. Shultz, Jeffrey L. Elman
164
Voted
NIPS
2007
15 years 6 months ago
Gaussian Process Models for Link Analysis and Transfer Learning
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...
Kai Yu, Wei Chu
CIBCB
2007
IEEE
15 years 11 months ago
Motifs and Modules in Fractured Functional Yeast Networks
The integration of diverse data sets into probabilistic functional networks is an active and important area of research in systems biology. In this paper we fracture a previously p...
Jennifer Hallinan, Anil Wipat
KDD
2009
ACM
132views Data Mining» more  KDD 2009»
16 years 5 months ago
Learning patterns in the dynamics of biological networks
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
Chang Hun You, Lawrence B. Holder, Diane J. Cook