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Boolean Networks as Predictive Models of Emergent Biological Behaviors
Modeling these systems is made challenging by the number and variety of biological components and interactions (from molecules in gene regulatory networks to species in ecological networks) and the often-incomplete state of system knowledge (e. g., the unknown values of kinetic parameters for biochemical reactions).
Analysis of SVM with Indefinite Kernels
The recent introduction of indefinite SVM by Luss and dAspremont [15] has effectively demonstrated SVM classification with a non-positive semi-definite kernel (indefinite kernel).
Sparse Metric Learning via Smooth Optimization
From this saddle representation, we develop an efficient smooth optimization approach for sparse metric learning although the learning model is based on a non-differential loss function.
