Results 31 to 40 of about 10,830,582 (300)
Influence Selection for Active Learning [PDF]
IEEE International Conference on Computer Vision, 2021 The existing active learning methods select the samples by evaluating the sample’s uncertainty or its effect on the diversity of labeled datasets based on different task-specific or model-specific criteria.
Zhuoming Liu +5 more
semanticscholar +1 more source
Learning to Sample: An Active Learning Framework [PDF]
2019 IEEE International Conference on Data Mining (ICDM), 2019 Meta-learning algorithms for active learning are emerging as a promising paradigm for learning the ``best'' active learning strategy. However, current learning-based active learning approaches still require sufficient training data so as to generalize meta-learning models for active learning.
Jingyu Shao +2 more
openaire +2 more sources
Active Learning for Deep Visual Tracking [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 Convolutional neural networks (CNNs) have been successfully applied to the single target tracking task in recent years. Generally, training a deep CNN model requires numerous labeled training samples, and the number and quality of these samples directly ...
Di Yuan +4 more
semanticscholar +1 more source
Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 Active learning promises to alleviate the massive data needs of supervised machine learning: it has successfully improved sample efficiency by an order of magnitude on traditional tasks like topic classification and object recognition.
Siddharth Karamcheti +3 more
semanticscholar +1 more source
Semi-Supervised Active Learning with Temporal Output Discrepancy [PDF]
IEEE International Conference on Computer Vision, 2021 While deep learning succeeds in a wide range of tasks, it highly depends on the massive collection of annotated data which is expensive and time-consuming.
Siyu Huang +4 more
semanticscholar +1 more source
Active learning enabled activity recognition [PDF]
Pervasive and Mobile Computing, 2016 © 2016 IEEE, 2016 IEEE International Conference on Pervasive Computing and Communications (PerCom)
H. M. Sajjad Hossain +2 more
openaire +1 more source
Journal of Cleaner Production, 2021 Effective Education for Sustainable Development (ESD) requires appropriate pedagogies that engage learners in transformative learning. These pedagogies include reflective and active learning, involving experiential, collaborative and learner-centred ...
semanticscholar +1 more source
The MLIP package: moment tensor potentials with MPI and active learning [PDF]
Machine Learning: Science and Technology, 2020 The subject of this paper is the technology (the ‘how’) of constructing machine-learning interatomic potentials, rather than science (the ‘what’ and ‘why’) of atomistic simulations using machine-learning potentials. Namely, we illustrate how to construct
I. Novikov +3 more
semanticscholar +1 more source
Eating habits matter for sleep difficulties in children and adolescents: A cross-sectional study
Frontiers in Pediatrics, 2023 BackgroundSleep difficulties are a common sleep-related problem among children and adolescents. However, the association between eating habits and sleep difficulties has not been extensively studied.
Yaping Zhao +5 more
doaj +1 more source
Active Function Learning [PDF]
, 2018 Abstract How do people actively explore to learn about functional relationships, that is, how continuous inputs map onto continuous outputs? We introduce a novel paradigm to investigate information search in continuous, multi-feature function learning scenarios.
Jones, Angela +3 more
openaire +5 more sources