CoSP: co-selection pick for a global explainability of black box machine learning models
出版年份 2023 全文链接
标题
CoSP: co-selection pick for a global explainability of black box machine learning models
作者
关键词
-
出版物
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS
Volume -, Issue -, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2023-10-18
DOI
10.1007/s11280-023-01213-8
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Evaluating explainability for graph neural networks
- (2023) Chirag Agarwal et al. Scientific Data
- Reinforced Causal Explainer for Graph Neural Networks
- (2022) Xiang Wang et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Optimising for Interpretability: Convolutional Dynamic Alignment Networks
- (2022) Moritz Böhle et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- A Survey on the Explainability of Supervised Machine Learning
- (2021) Nadia Burkart et al. JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
- Deep Learning--based Text Classification
- (2021) Shervin Minaee et al. ACM COMPUTING SURVEYS
- Artificial Intelligence Applications in Military Systems and Their Influence on Sense of Security of Citizens
- (2021) Marta Bistron et al. Electronics
- Similarity preserving feature generating networks for zero-shot learning
- (2020) Yuanbo Ma et al. NEUROCOMPUTING
- Overview: Computer Vision and Machine Learning for Microstructural Characterization and Analysis
- (2020) Elizabeth A. Holm et al. METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE
- sCOs: Semi-Supervised Co-Selection by a Similarity Preserving Approach
- (2020) Khalid Benabdeslem et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- DARPA’s Explainable Artificial Intelligence (XAI) Program
- (2019) David Gunning et al. AI MAGAZINE
- Interpreting Deep Visual Representations via Network Dissection
- (2018) Bolei Zhou et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Unsupervised feature selection based on self-representation sparse regression and local similarity preserving
- (2017) Ronghua Shang et al. International Journal of Machine Learning and Cybernetics
- Explaining prediction models and individual predictions with feature contributions
- (2013) Erik Štrumbelj et al. KNOWLEDGE AND INFORMATION SYSTEMS
- A scalable approach to simultaneous evolutionary instance and feature selection
- (2012) Nicolás García-Pedrajas et al. INFORMATION SCIENCES
- On Similarity Preserving Feature Selection
- (2011) Zheng Zhao et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- A review of instance selection methods
- (2010) J. Arturo Olvera-López et al. ARTIFICIAL INTELLIGENCE REVIEW
- IFS-CoCo: Instance and feature selection based on cooperative coevolution with nearest neighbor rule
- (2009) Joaquín Derrac et al. PATTERN RECOGNITION
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