Optimization Distance Learning Computer of Network
نویسندگان
چکیده
منابع مشابه
the impact of computer-assisted language learning on achievement motivation of high school students
چکیده انگیزه دلیل اصلی رفتارهای ما است. به نظر می رسد انگیزه جزء جدایی ناپذیر فرایند یادگیری باشد. ارزش ذاتی موفقیت تمایل به پیشرفت را در یادگیرنده ایجاد میکند. به عبارت ساده این تمایل انگیزه پیشرفت نامیده میشود. انگیزه پیشرفت را میتوان در احساس یادگیرنده هنگام چالش با درس های مدرسه، لذت انجام فعالیت درسی، یا حس کشف پاسخ مشاهده کرد.حتی ممکن است انگیزه پیشرفت را در تلاش یادگیرنده برای جلب تایید...
Computer systems for distributed and distance learning
Network-based learning is now such an important area that it would seem timely to examine progress to date and to draw conclusions regarding the direction of further research. This paper is the result of a survey of computer systems for distributed and distance learning, focusing on projects that help to illustrate the evolution of this important field. An examination such as this is important ...
متن کاملDistance Metric Learning with Eigenvalue Optimization
The main theme of this paper is to develop a novel eigenvalue optimization framework for learning a Mahalanobis metric. Within this context, we introduce a novel metric learning approach called DML-eig which is shown to be equivalent to a well-known eigenvalue optimization problem called minimizing the maximal eigenvalue of a symmetric matrix (Overton, 1988; Lewis and Overton, 1996). Moreover, ...
متن کاملDistance Metric Learning Through Convex Optimization
We present a survey of recent work on the problem of learning a distance metric in the framework of semidefinite programming (SDP). Along with a brief theoretical background on convex optimization and distance metrics, we present various methods developed in this context under different approaches and provide theoretical analysis for a subset of them. A gradient ascent projection algorithm (Xin...
متن کاملLearning a Distance Metric from a Network
Many real-world networks are described by both connectivity information and features for every node. To better model and understand these networks, we present structure preserving metric learning (SPML), an algorithm for learning a Mahalanobis distance metric from a network such that the learned distances are tied to the inherent connectivity structure of the network. Like the graph embedding a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computer Engineering and Applications Journal
سال: 2019
ISSN: 2252-5459,2252-4274
DOI: 10.18495/comengapp.v8i1.271