We propose a unifying approach that starts from the perturbative construction of trivializing maps by L\"uscher and then improves on it learning. The resulting continuous normalizing flow model can be implemented using common tools lattice field theory requires several orders magnitude fewer parameters than any existing machine learning approach. Specifically, our achieve competitive performanc...

Abstract: Performances of supervised machine learning will be affected by noises of labeled data badly, which has been well studied by existing theories about learning with noisy data. However these theories only focus on two-class classification problems. In this paper we studied the relation between noise examples and their effects on structured learning. Firstly, we found that noises of labe...

Learning curves have been proposed as an adequate description of learning processes, no matter whether the processes manifest within minutes or across years. Different mechanisms underlying skill acquisition can lead to differences in the shape of learning curves. In the current study, we analyze the tournament performance data of 1383 chess players who begin competing at young age and play tou...

Sociocultural theories of learning such as Wenger and Lave’s situated learning have been suggested as alternatives to cognitive theories of learning like constructivism. This article examines situated learning within the context of computer science (CS) education. Situated learning accurately describes some CS communities like open-source software development, but it is not applicable to other ...

Background & Objective: This study contributed to the current body of literature on educational games by comparing medical students’ flow experience in three types of educational games developed based on three learning theories: behavioral, cognitive, and social. Materials & Methods: A quasi-experimental repeated measure design was employed. A total of 39 second-year medical students played th...