Individualized help for at-risk students using model-agnostic and counterfactual explanations
Sign Up to like & getrecommendations! Published in 2021 at "Education and Information Technologies"
DOI: 10.1007/s10639-021-10661-6
Abstract: Although using machine learning for predicting which students are at risk of failing a course is indeed valuable, how can we identify which characteristics of individual students contribute to their being At-Risk? By characterising individual… read more here.
Keywords: agnostic counterfactual; risk; risk students; model agnostic ... See more keywords
Visual analysis of meteorological satellite data via model-agnostic meta-learning
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DOI: 10.1007/s12650-020-00704-4
Abstract: Abstract Satellites detect the distribution of meteorological data worldwide. However, due to the orbital constraints, the satellite can only reach the same area again after one orbiting cycle. The interval between two detections in the… read more here.
Keywords: model agnostic; satellite data; model; meteorological satellite ... See more keywords
Predicting dengue importation into Europe, using machine learning and model-agnostic methods
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DOI: 10.1038/s41598-020-66650-1
Abstract: The geographical spread of dengue is a global public health concern. This is largely mediated by the importation of dengue from endemic to non-endemic areas via the increasing connectivity of the global air transport network.… read more here.
Keywords: machine learning; model agnostic; dengue importation; importation ... See more keywords
A Model-Agnostic Feature Attribution Approach to Magnetoencephalography Predictions Based on Shapley Value
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2023.3248139
Abstract: Deep learning has greatly enhanced the predictive performance of magnetoencephalography (MEG) decoding. However, the lack of interpretability has become a major obstacle to the practical application of deep learning-based MEG decoding algorithms, which may lead… read more here.
Keywords: attribution approach; model agnostic; feature attribution; attribution ... See more keywords
TRUST XAI: Model-Agnostic Explanations for AI With a Case Study on IIoT Security
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3122019
Abstract: Despite artificial intelligence (AI)’s significant growth, its “black box” nature creates challenges in generating adequate trust. Thus, it is seldom utilized as a standalone unit in IoT high-risk applications, such as critical industrial infrastructures, medical… read more here.
Keywords: xai; model agnostic; trust; trust xai ... See more keywords
A Model-Agnostic Approach to Mitigate Gradient Interference for Multi-Task Learning.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3223377
Abstract: Multitask learning (MTL) is a powerful technique for jointly learning multiple tasks. However, it is difficult to achieve a tradeoff between tasks during iterative training, as some tasks may compete with each other. Existing methods… read more here.
Keywords: gradient interference; task; model agnostic;
Generalization on Unseen Domains via Model-Agnostic Learning for Intelligent Fault Diagnosis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3152316
Abstract: Machine learning-based diagnosis methods have achieved remarkable success under the assumption that the training and test data are identically distributed. However, a critical requirement of these methods is the generalization capability to unseen domains when… read more here.
Keywords: unseen domains; diagnosis; agnostic learning; model agnostic ... See more keywords
Unbiased Model-Agnostic Metalearning Algorithm for Learning Target-Driven Visual Navigation Policy
Sign Up to like & getrecommendations! Published in 2021 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2021/5620751
Abstract: As deep reinforcement learning methods have made great progress in the visual navigation field, metalearning-based algorithms are gaining more attention since they greatly improve the expansibility of moving agents. According to metatraining mechanism, typically an… read more here.
Keywords: agnostic metalearning; visual navigation; navigation; model ... See more keywords
Local Interpretable Model-Agnostic Explanations for Classification of Lymph Node Metastases
Sign Up to like & getrecommendations! Published in 2019 at "Sensors"
DOI: 10.3390/s19132969
Abstract: An application of explainable artificial intelligence on medical data is presented. There is an increasing demand in machine learning literature for such explainable models in health-related applications. This work aims to generate explanations on how… read more here.
Keywords: explanations classification; model agnostic; agnostic explanations; interpretable model ... See more keywords