Titlebook: Big Data, Cloud Computing, and Data Science Engineering; Roger Lee Book 2020 Springer Nature Switzerland AG 2020 Computational Intelligenc

critic

Multi-task Deep Reinforcement Learning with Evolutionary Algorithm and Policy Gradients Method in 3e amount of exploration may be limited. Therefore, it is considered effective to learn on source tasks that were previously for promoting learning on the target tasks. Existing researches have proposed pretraining methods for learning parameters that enable fast learning on multiple tasks. However,

falsehood

泰然自若

熔巖

A Survival Analysis-Based Prioritization of Code Checker Warning: A Case Study Using PMD,ecker whenever they change their source code to make sure that their code changes do not carry high risks of decreasing the code quality. Although code checkers would be helpful to detect risky code changes as early as possible, there is a practical problem which prevents an active utilization of su

creditor

,Elevator Monitoring System to Guide User’s Behavior by Visualizing the State of Crowdedness,ing sensors that send the data to a cloud. The cloud analyzes a set of the data, visualizes it and/or sends feedback to the “things.” However, there are many old facilities around us that were established in the past and do not have a sensing mechanism or the ability to send data, and so they become

Iatrogenic

Choice Behavior Analysis of Internet Access Services Using Supervised Learning Models, high-speed wireless services in Japan is growing rapidly in recent years. The choice behavior in the Internet-access service market is becoming complicated and diversified. We focus on two segments of Internet access users: fixed-line users and only-wireless users. Fixed-line users mean the custome