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Roughness, Harmony and Japanese Culture

Amaterasu-Omikami and Susanoo-no-Mikoto Takachiho in Miyazaki Prefecture is mentioned in the Kojiki (R...
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Recommendation systems in Netflix

  Netflix recommendation system The Netflix recommendation system will be based on information such as a user'...
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FIDO and Passkey

  FIDO FIDO (Fast Identity Online) is a standardisation framework for more secure and easier online authenticati...
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Overview of ChebNet and Examples of Algorithms and Implementations

Overview of ChebNet ChebNet (Chebyshev network) is a type of graph neural network (GNN) proposed by Deffer...
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Protected: Explainable Machine Learning (18)Adversarial Examples

Explainable Machine Learning with Adversarial Sample Approach utilized for Digital Transformation, Artificial Intelligence, and Machine Learning tasks Cyber Security, Surrogate Models, Neural Networks, Black Box Attack, Expectation Over Transformation algorithm, EOT, InceptionV3, TensorFlow, Fast gradient method, VGG16 classifier, ImageNet, adversarial patch, 1-pixel attack, L-BFGS method, Fast gradient sign method
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Protected: Explainable Artificial Intelligence (15) model-independent interpretation (sharpley value)

Model-independent interpretation with Sharpe Ray values as explainable artificial intelligence used for digital transformation, artificial intelligence, and machine learning tasks breakDown, fastshap, R language, symmetry axioms, LIME, SHAP, sparse explanation, efficiency, symmetry, dummy, additivity principle, Sharpe Ray values, cooperative game theory
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Protected: On-line Stochastic Optimization and Stochastic Dual Averaging (SDA) for Machine Learning

On-line stochastic optimization and stochastic dual averaging methods for machine learning (mirror image descent, strongly convex functions, convex functions, convergence rates, polynomial decay averaging, strongly convex regularization) for digital transformation, artificial intelligence and machine learning tasks.
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Evaluation of clustering for familiarization with k-means

On the evaluation of clustering around k-means for digital transformation, artificial intelligence, and machine learning tasks curse of dimensionality, Mahalanobis distance, Davies-Bouldin index, Dunn index, squared error, RSME, cluster number estimation, inter-cluster density, intra-cluster density
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KI 2017: Advances in Artificial Intelligence Papers

KI2017 In the previous article we discussed KI2016. In this issue, we describe KI2017, which w...
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KI 2014: Advances in Artificial Intelligence Papers

KI 2014: Advances in Artificial Intelligence In the previous article, we discussed KI2013. This time...
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