Search Results - interpretable constructive algorithm

An Interpretable Constructive Algorithm for Incremental Random Weight Neural Networks and Its Application by Nan, Jing, Dai, Wei, Yuan, Guan, Zhou, Ping

“… To address this gap, this article proposes an interpretable construction algorithm (ICA). Specifically, we first conduct a spatial geometric analysis of the network…”
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Asynchronous multisource alignment-driven real-time online detection of ash content in flotation clean coal by Wang, Lanhao, Liu, Jiahui, Dai, Wei, Gui, Xiahui, Wang, Hongyan

“… Second, an interpretable Constructive algorithm with response-weight…”
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Hierarchical Interpretable Construction Algorithm for Data Analysis by Dai, Wei, Duan, MingZi, Nan, Jing

“…In low-computation modeling tasks, the Incremental Constructive Algorithm (ICA) shows good performance…”
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Interpretable Neural Networks with Random Constructive Algorithm by Jing, Nan, Dai, Wei

“…This paper introduces an Interpretable Neural Network (INN) incorporating spatial information to tackle the opaque parameterization process of random weighted neural networks…”
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A hybrid linear–nonlinear model with two-stage feature selection for TiO2 content prediction in ilmenite based on XRF spectroscopy by Dai, Wei, Duan, Mingzi, Nan, Jing, Wang, Lanhao

“… due to matrix effects. Subsequently, this paper introduces a Stacked Interpretable Constructive Algorithm (SICA…”
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A general framework for interpretable neural learning based on local information-theoretic goal functions by Makkeh, Abdullah, Graetz, Marcel, Schneider, Andreas C, Ehrlich, David A, Priesemann, Viola, Wibral, Michael

“… Efforts to bring learning to a more local scale indeed lead to valuable insights, however, a general constructive approach to describe local learning goals that is both interpretable and adaptable…”
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Interpretable machine learning model for predicting acute kidney injury in critically ill patients by Li, Xunliang, Wang, Peng, Zhu, Yuke, Zhao, Wenman, Pan, Haifeng, Wang, Deguang

“…) in intensive care patients by applying interpretable, explainable artificial intelligence techniques…”
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Construction of an antidepressant priority list based on functional, environmental, and health risks using an interpretable mixup-transformer deep learning model by Sun, Peixuan, Liu, Huaishi, Zhao, Yuanyuan, Hao, Ning, Deng, Zhengyang, Zhao, Wenjin

“…As emerging pollutants, antidepressants (AD) must be urgently investigated for risk identification and assessment. This study constructed a…”
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Multi-level cognitive state classification of learners using complex brain networks and interpretable machine learning by He, Xiuling, Li, Yue, Xiao, Xiong, Li, Yingting, Fang, Jing, Zhou, Ruijie

“…) were designed based on a revised Bloom’s taxonomy and the Interactive-Constructive-Active–Passive framework and used with 31 college students…”
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Neural Shape Parsers for Constructive Solid Geometry by Sharma, Gopal, Goyal, Rishabh, Liu, Difan, Kalogerakis, Evangelos, Maji, Subhransu

“…Constructive solid geometry (CSG) is a geometric modeling technique that defines complex shapes by recursively applying boolean operations on primitives such as spheres and cylinders…”
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Learned Greedy Method (LGM): A novel neural architecture for sparse coding and beyond by Khatib, Rajaei, Simon, Dror, Elad, Michael

“…” machines that lack interpretability. A constructive remedy to this drawback is a systematic design of networks by unfolding well-understood iterative algorithms…”
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Assessing myocardial infarction severity from the urban environment perspective in Wuhan, China by Yao, Yao, Yin, Hanyu, Xu, Changwu, Chen, Dongsheng, Shao, Ledi, Guan, Qingfeng, Wang, Ruoyu

“… an advanced interpretable model, the random forest algorithm (RFA)-based SHapley Additive exPlanations (SHAP) model…”
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Construction of Deep ReLU Nets for Spatially Sparse Learning by Liu, Xia, Wang, Di, Lin, Shao-Bo

“…Training an interpretable deep net to embody its theoretical advantages is difficult but extremely important in the community of machine learning…”
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Learning Regular Expressions for Interpretable Medical Text Classification Using a Pool-based Simulated Annealing Approach by Tu, Chaofan, Cui, Menglin

“…In this paper, we propose a rule-based engine composed of high-quality and interpretable regular expressions for medical text classification…”
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Viscoelastic characterization of the human osteosarcoma cancer cell line MG-63 using a fractional-order zener model through automated algorithm design and configuration by Duque-Gimenez, Grecia C., Zambrano-Gutierrez, Daniel F., Rodriguez-Nieto, Maricela, Menchaca, Jorge Luis, Cruz-Duarte, Jorge M., Zárate-Triviño, Diana G., Avina-Cervantes, Juan Gabriel, Ortiz-Bayliss, José Carlos

“… This paper proposes an integrated framework that combines fractional modeling with automated algorithm design to fit force-relaxation data acquired through atomic force microscopy…”
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Transparency and accountability in AI decision support: Explaining and visualizing convolutional neural networks for text information by Kim, Buomsoo, Park, Jinsoo, Suh, Jihae

“… We claim that one of the promising and constructive efforts would be to design transparent and accountable artificial intelligence (AI…”
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Constructive Fuzzy Cognitive Map for Depression Severity Estimation by Sovatzidi, Georgia, Vasilakakis, Michael, Iakovidis, Dimitris K

“… (EEG). The introduced Constructive FCM (CFCM) utilizes features extracted by a Constructive Fuzzy Representation Model (CFRM…”
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A Survey on Medical Explainable AI (XAI): Recent Progress, Explainability Approach, Human Interaction and Scoring System by Sheu, Ruey-Kai, Pardeshi, Mayuresh Sunil

“… as (i) local and global methods for preprocessing, (ii) knowledge base and distillation algorithms, and (iii…”
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ADMM-SLPNet: A Model-Driven Deep Learning Framework for Symbol-Level Precoding by Yang, Junwen, Li, Ang, Liao, Xuewen, Masouros, Christos

“…Constructive interference (CI)-based symbol-level precoding (SLP) is an emerging downlink transmission technique for multi-antenna communications systems, and its low-complexity implementations are of practical importance…”
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Developing a Quality Flag for SAR Ocean Wave Spectrum Partitioning with Machine Learning by Benchaabane, Amine, Husson, Romain, Pinheiro, Muriel, Hajduch, Guillaume

“…Synthetic Aperture Radar (SAR) is one of the few instruments capable of providing high-resolution global two-dimensional (2D) measurements of ocean waves…”
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