Conveners
Artificial Intelligence
- Simon C. Lin (ASGC)
Artificial Intelligence
- Simon C. Lin (ASGC)
Software defect prediction is aimed at identifying defect prone software modules in order to allocate testing resources [1, 2]. In the development software life cycle, software testing plays an essential role: its criticality is proved by the significant amount of spending that companies allocate to it [3]. In the last decades, furthermore, software systems are becoming more and more complex...
In order to defend against complex threats and attacks in cyberspace, IHEPSOC has been developed and deployed at the Institute of High Energy Physics Chinese Academy of Sciences (IHEP), which is considered as an integrated security operation platform to ensure a secure state of the network and scientific researches in IHEP. Nowadays the integration of the state-of-the-art cyber-attack...
Transfer Learning technique has been successfully applied to many scientific fields such as computer vision, natural language processing, and so on. This presentation reports an enhancement of data analysis in collider physics experiments based on this Transfer Learning technique.
Experimental particle physics aims to understand the fundamental laws of nature using a huge amount of data. In...
In the synchrotron radiation tomography experiment, sparse-view sampling is capable of reducing severe radiation damages of samples from X-ray, accelerating sampling rate and decreasing total volume of the experimental dataset. Consequently, the sparse-view CT reconstruction has been a hot topic nowadays. Generally, there are two types of traditional algorithms for CT reconstruction, i.e., the...
The ML_INFN initiative (“Machine Learning at INFN”) is an effort to foster Machine Learning activities at the Italian National Institute for Nuclear Physics (INFN). In recent years, AI inspired activities have flourished bottom-up in many efforts in Physics, both at the experimental and theoretical level. Many researchers have procured desktop-level devices, with consumer oriented GPUs, and...
Since the breakthrough achieved by the DQN agent in 2013 and 2015 on the Atari learning environment - a benchmark that was thought to be feasible only for humans - Reinforcement Learning (RL) and, especially, its combination with Deep Learning (DL), called Deep Reinforcement Learning (DRL), have both gained a major interest in the field since then, likewise AlexNet (thanks to the...
