Self-paced learning with privileged information

Xu, Wei; Liu, Wei; Chi, Haoyuan; Song, Qi; Jin, Yu

doi:10.1016/j.neucom.2019.06.072

Cited by 21 publications

(2 citation statements)

References 4 publications

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“…Tullis et al [44] stated that SPL allows learners to follow learning preferences; in other words, learners can choose the form of learning outcomes, learning resources, learning needs, and learning styles. However, the core idea of SPL is to train models on simple samples first and then gradually add complex samples into consideration, which well simulates the learning process of humans and animals [59].…”

Section: Resultsmentioning

confidence: 99%

Preliminary Analysis on Entertaining Educational Content for Learners With Autism Spectrum Disorder

Miaomiao,

Ariffin,

Hammuzamer

2024

tvujs

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This paper reports on an ongoing study regarding the needs of autism spectrum disorder learners for entertaining learning materials. Previous researchers have introduced a number of assistive technologies, but the use of assistive technologies is problematic for students with autism spectrum disorder. The lack of entertaining learning material for autism spectrum disorder students may be one of the reasons. Therefore, this study proposed student–entred learning and self–paced learning approaches to better help autism spectrum disorder students for learning. The methods of fieldwork and semistructured interviews were utilized to investigate the needs of autism spectrum disorder learners for entertaining learning materials. During the fieldwork, the favorite or main leisure activities at home of the participants were collected. Semi-structured interviews were conducted with teachers in special schools to investigate students’ needs for entertaining learning materials. The study results indicated that there are very few entertaining learning materials developed specifically for learners with autism spectrum disorder, but the need is urgent.

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Section: Resultsmentioning

confidence: 99%

Preliminary Analysis on Entertaining Educational Content for Learners With Autism Spectrum Disorder

Miaomiao,

Ariffin,

Hammuzamer

2024

tvujs

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“…For support vector machines with different tasks, the version of privileged information learning is introduced. Xu et al (2019) proposed an autonomous learning model using privileged information. Liang and Cherkassky (2007) used group information as privileged information.…”

Section: Introductionmentioning

confidence: 99%

Multi-view support vector machines with sub-view learning

et al. 2023

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Multi-view learning improves the performance of existing learning tasks by using complementary information between multiple feature sets. In the latest research, multi-view learning model using privilege information is proposed, specific models such as PSVM-2V and MCPK. In these models, views complement each other by acting as privileged information policies, However, a single view contains privilege information that can guide the classifier, and the existing framework does not consider it. In order to use this information to correct multi-view support vector machine classifier, we propose a framework for generating a series of small-scale views based on information hidden in a single view, which extends the original multi-view parallel structure to a hierarchical structure with sub-view mechanism. In this paper, two sub-view learning structures SL-PSVM-2V and SL-MCPK are constructed. The two new models fully exploit the data features in the view. Similarly, they follow the principles of consistency and complementarity. We use the standard quadratic programming solver to solve the new model. In 55 groups of classification experiments and noise sensitivity tests, the new model has better performance than the benchmark model. Statistical comparison shows that the new method is significantly different from the existing methods.

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Withdrawals Prediction in Virtual Learning Environments with Deep Self-paced Learning

Xie

2023

Communications in Computer and Information Science

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Self-paced learning with privileged information

Cited by 21 publications

References 4 publications

Preliminary Analysis on Entertaining Educational Content for Learners With Autism Spectrum Disorder

Preliminary Analysis on Entertaining Educational Content for Learners With Autism Spectrum Disorder

Multi-view support vector machines with sub-view learning

Withdrawals Prediction in Virtual Learning Environments with Deep Self-paced Learning

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