ICT技術:ICT Technology Overview of Git and easy usage and reference books
Summary
Git is a source code version control system that allows multiple people to work ...
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Deux Ex Machina
ICT技術:ICT Technology 旅 On the Road: Honjo and Fukagawa neighborhoods
Ryotaro Shiba's Road to Honjo and Fukagawa Sumida River Bridge, Tsukiji Bridge, Kachidokibashi Bridge, Tsukuda Bridge, Chuo Bridge, Eitai Bridge, Sumida River Bridge, New Bridge, Kiyosubashi Bridge, Ryogoku Bridge, Kuramae Bridge, Stable Bridge, Komagata Bridge, Azuma Bridge, Kototoi Bridge, Sakura Bridge, Monkey Punch, Lupin III, Kitamura So, Kaijin Nijumenso Den, Gisatsu, Rat Boy Jirokichi, Kanjin Sumo, and Tomioka Hachimangu Shrine, Fukagawa Festival, Tsunayoshi Tokugawa, Iemitsu Tokugawa, Pilgrimage to Mt. Daisen, Ohiko Bando, Bunshichi Genkai, Classic Rakugo, Yumi, Inase, Iki, Okyan, Natsume Soseki, Botchan, Tatsumi geisha
哲学:philosophy Protected: Special Lecture, “The Purpose of Philosophy,” from “Socrates in Defense.”
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アルゴリズム:Algorithms Protected: Optimal arm bandit and Bayesian optimal when the player’s candidate actions are huge or continuous (2)
Bayesian optimization for digital transformation, artificial intelligence, machine learning tasks and bandit when player behavior is massive/continuous Markov chain Monte Carlo, Monte Carlo integration, turn kernels, scale parameters, Gaussian kernels, covariance function parameter estimation, Simultaneous Optimistic Optimazation policy, SOO strategy, algorithms, GP-UCB policy, Thompson's law, expected value improvement strategy, GP-UCB policy
アルゴリズム:Algorithms Protected: Sparse Machine Learning with Overlapping Sparse Regularization
Sparse machine learning with overlapping sparse regularization for digital transformation, artificial intelligence, and machine learning tasks main problem, dual problem, relative dual gap, dual norm, Moreau's theorem, extended Lagrangian, alternating multiplier method, stopping conditions, groups with overlapping L1 norm, extended Lagrangian, prox operator, Lagrangian multiplier vector, linear constraints, alternating direction multiplier method, constrained minimization problem, multiple linear ranks of tensors, convex relaxation, overlapping trace norm, substitution matrix, regularization method, auxiliary variables, elastic net regularization, penalty terms, Tucker decomposition Higher-order singular value decomposition, factor matrix decomposition, singular value decomposition, wavelet transform, total variation, noise division, compressed sensing, anisotropic total variation, tensor decomposition, elastic net
機械学習:Machine Learning Linear Algebra Overview and Library and Reference Books
Linear Algebra and Machine Learning
Linear algebra is a field of mathematics that uses vectors and matrices to...
アルゴリズム:Algorithms Protected: Optimization for the main problem in machine learning
Optimization for main problems in machine learning used in digital transformation, artificial intelligence, and machine learning tasks (barrier function method, penalty function method, globally optimal solution, eigenvalues of Hesse matrix, feasible region, unconstrained optimization problem, linear search, Lagrange multipliers for optimality conditions, integration points, effective constraint method)
アルゴリズム:Algorithms Protected: Applied Bayesian inference in non-negative matrix factorization: model construction and inference
Non-negative matrix factorization as a construction and inference of applied Bayesian inference models used in digital transformation, artificial intelligence, and machine learning tasks Poisson distribution, latent variable, gamma distribution, approximate posterior distribution, variational inference, spectogram of organ performance data, missing value interpolation, restoration of high frequency components, super-resolution, graphical models, hyperparameters, modeling, auxiliary variables, linear dimensionality reduction, recommendation algorithms, speech data, Fast Fourier Transform, natural language processing
哲学:philosophy Protected: From the Special Lecture “Socrates’ Defense,” “Starting Points in Philosophy.”
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Uncategorized 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