Related papers: Architecture for Integrating Learning Platforms Us…
This study contributes to the literature by considering the difference in vocabulary used to express document content and information needs. Users are integrated into all research phases in order to provide them with relevant information…
End-to-end autonomous driving aims to build a fully differentiable system that takes raw sensor data as inputs and directly outputs the planned trajectory or control signals of the ego vehicle. State-of-the-art methods usually follow the…
This is the era of Information and Communication Technology (ICT). Nowadays, there is no limit to learn, people can learn anywhere and anytime with the enhancement of technology. Electronic Learning (E-learning) and Mobile Learning…
Recently, Large Language Models (LLMs) have achieved amazing zero-shot learning performance over a variety of Natural Language Processing (NLP) tasks, especially for text generative tasks. Yet, the large size of LLMs often leads to the high…
Recent breakthroughs in deep learning and artificial intelligence technologies have enabled numerous mobile applications. While traditional computation paradigms rely on mobile sensing and cloud computing, deep learning implemented on…
In the paper, we propose a novel methodology to map learning algorithms on data (performance map) in order to gain more insights in the distribution of their performances across their parameter space. This methodology provides useful…
The research objective is to design a blended learning of system programming for software engineering bachelors. Under blended learning we understand the way of implementing the content of the training, which integrates classroom and…
The acquisition of non-proprietary and proprietary learning management system has provided a richer learning experience to users and raised interest among education providers. This study aims to assess student adoption of Canvas as a new…
In this study, we investigate learning rate adaption at different levels based on the hyper-gradient descent framework and propose a method that adaptively learns the optimizer parameters by combining multiple levels of learning rates with…
E-learning; enhanced by communicating and interacting is becoming increasingly accepted and this puts Web 2.0 at the center of the new educational technologies. E-Learning 2.0 emerges as an innovative method of online learning for its…
As educational technology evolves, the potential of Pedagogical Agents (PAs) in supporting education is extensively explored. Typically, research on PAs has primarily focused on computer-based learning environments, but their use in…
Federated learning becomes increasingly attractive in the areas of wireless communications and machine learning due to its powerful functions and potential applications. In contrast to other machine learning tools that require no…
Every teacher understands that different students benefit from different activities. Recent advances in data processing allow us to detect and use behavioral variability for adapting to a student. This approach allows us to optimize…
The transformer is a neural network component that can be used to learn useful representations of sequences or sets of data-points. The transformer has driven recent advances in natural language processing, computer vision, and…
Web and internet computing is evolving into a combination of social media, mobile, analytics and cloud (SMAC) solutions. There is a need for an integrated approach when developing solutions that address web scale requirements with…
Educators are more than workers within educational systems; they are stewards of educational systems. They must analyze student performance data, identify patterns that inform targeted interventions and personalized learning plans,…
We study the process of multi-agent reinforcement learning in the context of load balancing in a distributed system, without use of either central coordination or explicit communication. We first define a precise framework in which to study…
The educational landscape of Afghanistan, besieged by infrastructural inadequacies and socio-political tribulations, presents a compelling case for the integration of mobile learning platforms. This article embarks on an exploratory voyage…
The classical machine learning paradigm requires the aggregation of user data in a central location where machine learning practitioners can preprocess data, calculate features, tune models and evaluate performance. The advantage of this…
Transformer becomes the state-of-the-art translation model, while it is not well studied how each intermediate component contributes to the model performance, which poses significant challenges for designing optimal architectures. In this…