Published in Journal of Artificial General Intelligence
In 2011, Hibbard suggested an intelligence measure for agents who compete in an adversarial sequence prediction game. We argue that Hibbard’s idea should actually be considered as two separate ideas: first, that the intelligence of such agents can be measured based on the growth rates of the runtimes of the competitors that they defeat; and second,...
Stochastic optimization methods encounter new challenges in the realm of streaming, characterized by a continuous flow of large, high-dimensional data. While first-order methods, like stochastic gradient descent, are the natural choice, they often struggle with ill-conditioned problems. In contrast, second-order methods, such as Newton's methods, o...
Many machine learning tasks can be solved by minimizing a convex function of an occupancy measure over the policies that generate them. These include reinforcement learning, imitation learning, among others. This more general paradigm is called the Concave Utility Reinforcement Learning problem (CURL). Since CURL invalidates classical Bellman equat...
Published in Neuromorphic Computing and Engineering
Understanding how biological neural networks carry out learning using spike-based local plasticity mechanisms can lead to the development of real-time, energy-efficient, and adaptive neuromorphic processing systems. A large number of spike-based learning models have recently been proposed following different approaches. However, it is difficult to ...
Published in Frontiers in Psychology
Introduction This study delves into the intricate network of motivational factors that influence online learning satisfaction among intermediate-level English as a Foreign Language (EFL) students in mainland China. Methods A diverse sample of 496 EFL students participated in this research. Structural Equation Modeling was employed as the analytical...
Published in Frontiers in Psychology
Research into metacognitive listening instruction under the Metacognitive Pedagogical Cycle (MPC) has been growing in recent decades, but its effects on L2 listening comprehension, metacognitive awareness, and self-efficacy remain inconclusive. In this mixed-method study, we developed a self-directed online listening practice based on the MPC and i...
Published in Frontiers in Oral Health
Dental education is rich with examples of innovation as educators have responded to advances in knowledge, technology, the needs of the community, and most recently the challenges of the COVID-19 pandemic. Current challenges requiring innovative pedagogies include developing graduates who are interprofessional collaborative practice-ready, adapting...
Published in Rheumatology (Oxford, England)
To examine the effect of pre-course e-learning on residents' practical performance in musculoskeletal ultrasound (MSUS). This was a multicentre, randomized controlled study following the Consolidated Standards of Reporting Trials (CONSORT) statement. Residents with no or little MSUS experience were randomized to either an e-learning group or a trad...
Published in Journal of American college health : J of ACH
We examined undergraduates' concerns about returning to campus and online learning from home. Undergraduates majoring in STEM (Science, Technology, Engineering, and Mathematics) at US universities/colleges. Participants completed an online survey in July 2020. We content-analyzed responses to open-ended questions about concerns about fall 2020. Stu...
Published in European journal of dental education : official journal of the Association for Dental Education in Europe
Modified teaching strategies (MTS), asynchronous online teaching and smaller dissection groups, were applied to a gross anatomy course for dental students in the National Taiwan University in April 2020 in response to the COVID-19 pandemic. This study aimed to investigate the effects and perceptions of MTS on dental students. Scores for anatomy exa...
