Detecting and predicting a program’s execution phases are crucial to dynamic optimizations and dynamically adaptable systems. This paper shows that a phase can be associated with...
Jinpyo Kim, Sreekumar V. Kodakara, Wei-Chung Hsu, ...
This paper focuses on hybrid systems whose discrete state transitions depend on both deterministic and stochastic events. For such systems, after introducing a suitable hybrid mod...
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
This paper proposed a modified algorithm, sequential niching particle swarm optimization (SNPSO), for the attempt to get multiple maxima of multimodal function. Based on the sequen...
Advances in SAT solver technology have enabled many automated analysis and reasoning tools to reduce their input problem to a SAT problem, and then to use an efficient SAT solver ...