Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
This paper proposes a novel hybrid GA/SVM method that can predict the interactions between proteins intermediated by the protein-domain relations. Firstly, we represented a protein...
Bing Wang, Lu-Sheng Ge, Wen-You Jia, Li Liu, Fu-Ch...
Concurrency, as a useful feature of many modern programming languages and systems, is generally hard to reason about. Although existing work has explored the verification of concu...
In this paper, we define a family of syntactic kernels for automatic relational learning from pairs of natural language sentences. We provide an efficient computation of such mode...
We propose a general framework for support vector machines (SVM) based on the principle of multi-objective optimization. The learning of SVMs is formulated as a multiobjective pro...