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BMCBI
2007
140views more  BMCBI 2007»
14 years 9 months ago
Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure in
Background: Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio...
Gianluca Pollastri, Alberto J. M. Martin, Catherin...
ICML
2008
IEEE
15 years 10 months ago
Laplace maximum margin Markov networks
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
Jun Zhu, Eric P. Xing, Bo Zhang
JMLR
2010
101views more  JMLR 2010»
14 years 4 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
ICML
2010
IEEE
14 years 10 months ago
Learning Temporal Causal Graphs for Relational Time-Series Analysis
Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
Yan Liu 0002, Alexandru Niculescu-Mizil, Aurelie C...
PKDD
2009
Springer
170views Data Mining» more  PKDD 2009»
15 years 4 months ago
Statistical Relational Learning with Formal Ontologies
Abstract. We propose a learning approach for integrating formal knowledge into statistical inference by exploiting ontologies as a semantically rich and fully formal representation...
Achim Rettinger, Matthias Nickles, Volker Tresp