Results 11 to 20 of about 44,296 (265)
A survey of large-scale graph-based semi-supervised classification algorithms
International Journal of Cognitive Computing in Engineering, 2022 Semi-supervised learning is an effective method to study how to use both labeled data and unlabeled data to improve the performance of the classifier, which has become the hot field of machine learning in recent years.
Yunsheng Song, Jing Zhang, Chao Zhang
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Learning to Learn in a Semi-supervised Fashion [PDF]
, 2020 To address semi-supervised learning from both labeled and unlabeled data, we present a novel meta-learning scheme. We particularly consider that labeled and unlabeled data share disjoint ground truth label sets, which can be seen tasks like in person re-identification or image retrieval.
Yun-Chun Chen +2 more
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Human Semi‐Supervised Learning [PDF]
Topics in Cognitive Science, 2013 AbstractMost empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real‐world learning scenarios, however, are semi‐supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a ...
Bryan R. Gibson +2 more
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Contrastive Semi-Supervised Learning for ASR [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 Pseudo-labeling is the most adopted method for pre-training automatic speech recognition (ASR) models. However, its performance suffers from the supervised teacher model's degrading quality in low-resource setups and under domain transfer. Inspired by the successes of contrastive representation learning for computer vision and speech applications, and ...
Alex Xiao +2 more
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Meta-Semi: A Meta-Learning Approach for Semi-Supervised Learning
CAAI Artificial Intelligence Research, 2022 Deep learning based semi-supervised learning (SSL) algorithms have led to promising results in recent years. However, they tend to introduce multiple tunable hyper-parameters, making them less practical in real SSL scenarios where the labeled data is ...
Yulin Wang +5 more
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International Journal of Applied Mathematics and Computer Science, 2023 Acoustic features of speech are promising as objective markers for mental health monitoring. Specialized smartphone apps can gather such acoustic data without disrupting the daily activities of patients.
Casalino Gabriella +6 more
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Information, 2021 Smart grids integrate advanced information and communication technologies (ICTs) into traditional power grids for more efficient and resilient power delivery and management, but also introduce new security vulnerabilities that can be exploited by ...
Ruobin Qi +3 more
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Pseudo-Labeling Optimization Based Ensemble Semi-Supervised Soft Sensor in the Process Industry
Sensors, 2021 Nowadays, soft sensor techniques have become promising solutions for enabling real-time estimation of difficult-to-measure quality variables in industrial processes.
Youwei Li +4 more
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Semi-supervised Learning Method Based on Automated Mixed Sample Data Augmentation Techniques [PDF]
Jisuanji kexue, 2022 Consistency-based semi-supervised learning methods typically use simple data augmentation methods to achieve consistent predictions for both original inputs and perturbed inputs.The effectiveness of this approach is difficult to be guaranteed when the ...
XU Hua-jie, CHEN Yu, YANG Yang, QIN Yuan-zhuo
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Semi‐supervised uncorrelated dictionary learning for colour face recognition
IET Computer Vision, 2020 Colour images are increasingly used in the fields of computer vision, pattern recognition and machine learning, since they can provide more identifiable information than greyscale images. Thus, colour face recognition has attracted accumulating attention.
Qian Liu +4 more
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