Machine-learning-assisted modeling

Machine learning algorithms in air quality modeling

Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...

Simulation assisted machine learning

Predicting how a proposed cancer treatment will affect a given tumor can be cast as a machine learning problem, but the complexity of biological systems, the number of potentially relevant genomic and clinical features, and the lack of very large scale patient data repositories make this a unique challenge. “Pure data” approaches to this problem are underpowered to detect combinatorially comple...

Machine Learning-Assisted Binary Code Analysis

Binary code analysis is a foundational technique in the areas of computer security, performance modeling, and program instrumentation. In computer security, such analysis can provide the basis for detecting, understanding and controlling malicious code. Any analysis of malicious program requires as a first step precisely locating the Function Entry Points (FEPs, the starting byte of each functi...

Modeling Language for Machine Learning

For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach. We sho...

Machine Learning in User Modeling