With the explosive growth of the use of imagery, visual recognition plays an important role in many applications and attracts increasing research attention. Given several related tasks, single-task learning learns each task separately and ignores the relationships among these tasks. Different from single-task learning, multi-task learning can explore more information to learn all tasks jointly ...

We introduce the underlying concepts which give rise to some of commonly used machine learning methods, excluding deep-learning machines and neural networks. point their advantages, limitations potential use in various areas photonics. The main methods covered include parametric non-parametric regression classification techniques, kernel-based support vector machines, decision trees, probabilis...

Ayurveda medicines uses herbs for curing many ailments without side effects. The biggest concern related to medicine is extinction of important medicinal herbs, which may be due insufficient knowledge, weather conditions, and urbanization. Another reason consists lack online facts on Indian because it dependent books experts. This has motivated in utilizing the machine learning techniques ident...

Prediction-based decisions, which are often made by utilizing the tools of machine learning, influence nearly all facets modern life. Ethical concerns about this widespread practice have given rise to field fair learning and a number fairness measures, mathematically precise definitions that purport determine whether prediction-based decision system is fair. Following Reuben Binns (2017), we ta...

The Journal of Smart Environments and Green Computing is an international, peer-reviewed, open access journal which provides a forum for the publication papers addressing variety theoretical, methodological, epistemological, empirical practical issues. following topics are especially welcome: green computing, sustainable energy efficiency, decision making, cloud smart cities, renewable energy, ...

Simultaneous matrix diagonalization is a key subroutine in many machine learning problems, including blind source separation and parameter estimation in latent variable models. Here, we extend joint diagonalization algorithms to low-rank and asymmetric matrices and also provide extensions to the perturbation analysis of these methods. Our results allow joint diagonalization to scale to larger p...

* Corresponding author. This work is supported by the National Natural Science Foundation of China under Grant 60303012 Abstract: In recent years, intrusion detection has emerged as an important technique for network security. Due to the large volumes of security audit data as well as complex and dynamic properties of intrusion behaviors, to optimize the performance of intrusion detection syste...