Frugal Optimization for Cost-related Hyperparameters

The increasing demand for democratizing machine learning algorithms calls for hyperparameter optimization (HPO) solutions at low cost. Many machine learning algorithms have hyperparameters which can cause a large variation in the training cost. But this effect is largely ignored in existing HPO methods, which are incapable to properly control cost during the optimization process. To address this problem, we develop a new cost-frugal HPO solution. The core of our solution is a simple but new randomized direct-search method, for which we prove a convergence rate of $O(\frac{\sqrt{d}}{\sqrt{K}})$ and an $O(d\epsilon^{-2})$-approximation guarantee on the total cost. We provide strong empirical results in comparison with state-of-the-art HPO methods on large AutoML benchmarks.Comment: 29 pages (including supplementary appendix

Development of the NTP Pool Project in Taiwan

Among the standard time reporting systems, the Network Time Protocol (NTP) provides an easy and accurate way for the accessing the Universal time. The NTP is taking the benefit of the pervasiveness of the computer network during the recent information-oriented modern world. The NTP Pool Project is the project to provide a distributed framework of the NTP servers. As the ever-increasing amounts of the requests of the standard time, the number of the NTP servers provided by the NTP Pool Project will be extended correspondingly. This paper will provide the detailed introduction on the framework of the NTP Pool Project, the development of the NTP Pool Project in Taiwan at the present time, and the followed by the suggestions of the implementation of the NTP pool project

THE CHANGE OF KNEE KINEMATICS AFTER ANTERIOR CRUCIATE LIGAMENT DEFICIENCY AND RECONSTRUCTION DURING LANDING

The purpose of this study were to evaluate the different of knee kinematics analysis after ACLD and ACLR during landing performances. The participants were instructed to finish counter moment jump (CMJ) with arms free 5 times as hard as possible with Vicon motion system and two force platforms. The ACLD showed a significant less knee flexion degree at the peak vertical GRF compared with others. Our founding was similar to the present studies; the impulse during landing among three groups was almost the same, but the RF EMG showed lower after two ACL groups, especially in ACLD

Constructivist Perspective on Developing a Multidimensional Blended Teaching Model Fostering Deep Learning

To promote high-quality development of higher education, it is imperative to facilitate students’ transition from surface learning to deep learning. Compared with surface learning that focuses on rote memorization, deep learning emphasizes meaningful learning based on understanding and transfer. It involves three progressively advanced cognitive stages of knowing: "learning for understanding," "learning for application," and "learning for innovation," which ultimately enable the internalization, transfer, and creative application of knowledge. How to foster deep learning in students has been an urgent issue of higher education. This study, grounded in constructivist learning theory, explores a multidimensional blended teaching model fostering deep learning. It also develops an evaluation system assessing learning outcomes from the perspectives of ideological, political and moral education, knowledge, and competencies. We conducted an empirical study to test the effectiveness of this multidimensional blended teaching model. Findings will provide theoretical and practical implications for teaching reforms of similar courses

Anisotropy characteristics of exposed gravel beds revealed in high-point-density airborne laser scanning data

The aim of this study was to examine the relationship between the anisotropy direction of exposed gravel bed and flow direction. Previous studies have shown that the anisotropy direction of a gravel bed surface can be visually determined in the elliptical contours of 2-D variogram surface (2DVS). In this letter, airborne laser scanning (ALS) point clouds were acquired at a gravel bed, and the whole data set was divided into a series of 6 m × 6 m subsets. To estimate the direction of anisotropy, we proposed an ellipse-fitting-based automatic procedure with consideration given to the grain size characteristic d50 to estimate the primary axis of anisotropy [hereafter referred to as the primary continuity direction (PCD)] in the 2DVS. The ALS-derived PCDs were compared to the flow directions (for both high and low flow) derived from hydrodynamic model simulation. Comparison of ALS-derived PCDs and simulated flow directions suggested that ALS-derived PCDs could be used to infer flow direction at different flow rates. Furthermore, we found that the ALS-derived PCDs estimated from any elliptical contour of the 2DVS exhibited a similar orientation when the contours of the 2DVS reveal the clear anisotropic structure, demonstrating the robustness of the technique