Many massive data are assembled through collections of information a large number individuals in population. The analysis such data, especially the aspect individualized inferences...

The performance of optimization algorithms, and consequently AI/machine learning solutions, is strongly influenced by the setting their hyperparameters. Over last decades, a rich literature has developed proposing methods to automatically determine parameter for problem interest, aiming at either robust or instance-specific settings. Robust already mature area research, while instance-level sti...

Because a self-regulated learning is a selfleading and a positive learning, it is referred to an ideal learning. The interest on an individualized and selfregulated e-learning system is more increasing. After making a contract process with the proposed system, learners can organize the individualized course based on the learner's demand and level. In this research, the selfregulated learning sy...

We establish a high-dimensional statistical learning framework for individualized asset allocation. Our proposed methodology addresses continuous-action decision-making with large number of characteristics. develop discretization approach to model the effect continuous actions and allow frequency be diverge observations. estimate value function using penalized regression our generalized penalti...

English language learners need individualized guidance and high efficiency in their autonomous learning. This paper discusses the design of an intelligent online autonomous learning platform for Chinese EFL learners from the perspectives of the principles applied, the materials chosen and the technology involved. Taking the Website of Shanghai Jiao Tong University English Learning Center as an ...