Model-Agnostic Utility-Preserving Biometric Information Anonymization
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Information Security"
DOI: 10.1007/s10207-024-00862-8
Abstract: The recent rapid advancements in both sensing and machine learning technologies have given rise to the universal collection and utilization of people’s biometrics, such as fingerprints, voices, retina/facial scans, or gait/motion/gestures data, enabling a wide… read more here.
Keywords: biometrics; information; model agnostic; utility ... See more keywords
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
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Visualization"
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
Sign Up to like & getrecommendations! Published in 2020 at "Scientific Reports"
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
Model-agnostic basis functions for the 2-point correlation function of dark matter in linear theory
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Cosmology and Astroparticle Physics"
DOI: 10.1088/1475-7516/2025/06/009
Abstract: We consider approximating the linearly evolved 2-point correlation function (2pcf) of dark matter ξ lin(r;θ) in a cosmological model with parameters θ as the linear combination ξ lin(r;θ)≈∑ i bi (r) wi (θ), where the… read more here.
Keywords: dark matter; model agnostic; basis; point correlation ... See more keywords
Identifying thermal effects in neutron star merger remnants with model-agnostic waveform reconstructions and third-generation detectors
Sign Up to like & getrecommendations! Published in 2024 at "Physical Review D"
DOI: 10.1103/physrevd.111.043006
Abstract: We probe the intrinsic differences in simulated gravitational-wave signals from binary neutron star (BNS) mergers, arising from varying approaches to incorporating thermal effects in numerical-relativity modeling. We consider a hybrid approach in which the equation… read more here.
Keywords: model agnostic; third generation; neutron star; merger ... 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;
Constructing Interpretable Belief Rule Bases Using a Model-Agnostic Statistical Approach
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Fuzzy Systems"
DOI: 10.1109/tfuzz.2024.3416448
Abstract: Belief rule base (BRB) has attracted considerable interest due to its interpretability and exceptional modeling accuracy. Generally, BRB construction relies on prior knowledge or historical data. The limitations of knowledge constrain the knowledge-based BRB and… read more here.
Keywords: brb; model agnostic; rule; rule bases ... See more keywords
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