Results 71 to 80 of about 11,928,939 (371)
SportsThis two-phase study involved the design, development, and evaluation of netball-specific high-intensity interval training sessions (Netball-HIIT) for use with netballers of varied ages and abilities.
Narelle Eather +3 more
doaj +1 more source
Active Learning Polynomial Threshold Functions [PDF]
arXiv, 2022 We initiate the study of active learning polynomial threshold functions (PTFs). While traditional lower bounds imply that even univariate quadratics cannot be non-trivially actively learned, we show that allowing the learner basic access to the derivatives of the underlying classifier circumvents this issue and leads to a computationally efficient ...
arxiv
Advancement of science, 2020 In recent years, machine learning (ML) techniques are seen to be promising tools to discover and design novel materials. However, the lack of robust inverse design approaches to identify promising candidate materials without exploring the entire design ...
Chun-Teh Chen, Grace X. Gu
semanticscholar +1 more source
An Active Structure that Learns [PDF]
Journal of Computing in Civil Engineering, 2005 Tensegrity structures are composed of cables and struts that become stable through self stress. They are good candidates for implementation of active structural control because their flexibility may mean that they cannot meet serviceability criteria. Changes to the self stress influence the form of the structure.
Domer, B., Smith, I.F.C.
openaire +3 more sources
Frontiers in Psychology, 2022 BackgroundPrevious studies have focused on the opposite relation between muscle strength, obesity, and depression in adults. Moreover, the evidence has indicated that obesity and depression in adults might be significantly decreased with Muscle Strength ...
Jizu Shi +5 more
doaj +1 more source
Learning to learn with active adaptive perception [PDF]
Neural Networks, 2019 Increasingly, autonomous agents will be required to operate on long-term missions. This will create a demand for general intelligence because feedback from a human operator may be sparse and delayed, and because not all behaviours can be prescribed. Deep neural networks and reinforcement learning methods can be applied in such environments but their ...
D.M. Bossens, N.C. Townsend, A.J. Sobey
openaire +4 more sources
SAGE Open, 2016 This article presents findings from a survey of the experiences of child protection workers in England when working with parents who exhibit aggression and violence. This work explores the effects on workers in their professional lives, and on themselves
Brian Littlechild +5 more
doaj +1 more source
Frontiers in Public Health, 2023 PurposePast studies have illustrated that the impact of sports participation on school-attending students’ well-being plays a significant role in the life course of adolescence, which is a golden period for developing sound psychological qualities ...
Tianzhuo Liu +5 more
doaj +1 more source
Stopping Criterion for Active Learning Based on Error Stability [PDF]
arXiv, 2021 Active learning is a framework for supervised learning to improve the predictive performance by adaptively annotating a small number of samples. To realize efficient active learning, both an acquisition function that determines the next datum and a stopping criterion that determines when to stop learning should be considered.
arxiv
Activation Functions: Dive into an optimal activation function [PDF]
arXiv, 2022 Activation functions have come up as one of the essential components of neural networks. The choice of adequate activation function can impact the accuracy of these methods. In this study, we experiment for finding an optimal activation function by defining it as a weighted sum of existing activation functions and then further optimizing these weights ...
arxiv