Multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. Our goal is to make use of the multi-core as well as multi...
Lei Li, Wenjie Fu, Fan Guo, Todd C. Mowry, Christo...
Transformation of both the response variable and the predictors is commonly used in fitting regression models. However, these transformation methods do not always provide the maxi...
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...