Mitigating belief projection in explainable artificial intelligence via Bayesian teaching

Yang, Scott Cheng‐Hsin; Vong, Wai Keen; Sojitra, Ravi B.; Folke, Tomas; Shafto, Patrick

doi:10.1038/s41598-021-89267-4

Cited by 36 publications

(35 citation statements)

References 32 publications

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“…e technical research related to online learning mainly covers the design and support services of learning system components and platforms. e research in the field of application focuses on the teaching mode, teaching strategy, and teaching application of online learning, and the literature [8] studies the design process of the contextual experience course. At present, the evaluation system and management research of online learning are relatively small, and it rarely involves the funds, market operation, and management of the online learning system.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] International Chinese Education Expert System Based on Artificial Intelligence and Machine Learning Algorithms

Shen

Latif

2022

Journal of Mathematics

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This study builds an international Chinese education expert system based on artificial intelligence and machine learning algorithms, introduces interval intuition fuzzy sets to express expert evaluation information, and uses the entropy weight method to determine the weight of evaluation attributes in order to improve the effect of international Chinese teaching and learning. The group utility value, personal regret value, and comprehensive evaluation value of each system are then calculated in this study. At the same time, this study introduces the degree of closeness and satisfaction to improve the decision-making process and finally determines the optimal solution. In addition, this study constructs an intelligent system based on the improved algorithm. The research shows that the international Chinese education expert system based on artificial intelligence and machine learning algorithm proposed in this study has a very good effect.

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Section: Related Workmentioning

confidence: 99%

[Retracted] International Chinese Education Expert System Based on Artificial Intelligence and Machine Learning Algorithms

Shen

Latif

2022

Journal of Mathematics

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“…Adult literacy rate, market productivity level, and other dimensions. Literature [10] constructs a multi-level measurement index system from four dimensions affecting educational equity.…”

Section: Related Workmentioning

confidence: 99%

Analysis on the Development Strategy of Private Education Based on Data Mining Algorithm

Xing

Maia

2022

Mathematical Problems in Engineering

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In order to improve the development effect of private education, this paper analyzes the current situation of private education combined with the data mining algorithm and explores the problems existing in the development of private education. Moreover, this paper combines the semi-parametric product estimation method with parameter estimation and applies the estimation method to model-assisted sampling estimation. This work enhances the estimate accuracy of the sample estimation and increases the field of application of the model while enhancing the classic generalized regression estimation. It also modifies the estimation accuracy on the basis of the linear assumption. The experimental study reveals that the data mining algorithm-based analysis approach for private education development provided in this work has a certain impact, and the development strategy of private education is assessed on this premise.

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“…Algorithmic teaching similarly investigates the problem of teaching but within the deterministic algorithmic learning framework [Doliwa et al, 2014]. Bayesian teaching has been investigated with standard probabilistic machine learning algorithms [Eaves Jr andShafto, 2016, Yang andShafto, 2017]. All of these assume that the relevant data are points, rather than more structured data and all require that the teacher knows the correct answer.…”

Section: Related Workmentioning

confidence: 99%

Learning a manifold from a teacher's demonstrations

Wang,

Givchi,

Shafto

2019

Preprint

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We consider the problem of manifold learning. Extending existing approaches of learning from randomly sampled data points, we consider contexts where data may be chosen by a teacher. We analyze learning from teachers who can provide structured data such as points, comparisons (pairs of points), demonstrations (sequences). We prove results showing that the former two do not yield notable decreases in the amount of data required to infer a manifold. Teaching by demonstration can yield remarkable decreases in the amount of data required, if we allow the goal to be teaching up to topology. We further analyze teaching learners in the context of persistence homology. Teaching topology can greatly reduce the number of datapoints required to infer correct geometry, and allows learning from teachers who themselves do not have full knowledge of the true manifold. We conclude with implications for learning in humans and machines.

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Mitigating belief projection in explainable artificial intelligence via Bayesian teaching

Cited by 36 publications

References 32 publications

[Retracted] International Chinese Education Expert System Based on Artificial Intelligence and Machine Learning Algorithms

[Retracted] International Chinese Education Expert System Based on Artificial Intelligence and Machine Learning Algorithms

Analysis on the Development Strategy of Private Education Based on Data Mining Algorithm

Learning a manifold from a teacher's demonstrations

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