2023-01

アーキテクチャ

AWS Cloud Service Design Patterns (2)

AWS Cloud Service Design Patterns used for Digital Transformation, Artificial Intelligence and Machine Learning tasks (Data Upload Patterns, Write Proxy, Storage Index, Direct Object Upload, Relational Database Patterns, DB Replication, Read Replica, Inmemory DB Cache, Sharing Write, Asynchronous Processing, Batch Processing Patterns, Queuing Chain, Priority Queue, Job Observer, Fanout)
アルゴリズム:Algorithms

Protected: An example of machine learning by Bayesian inference: inference by Gibbs sampling of a Poisson mixture model

Examples of machine learning with Bayesian inference utilized for digital transformation, artificial intelligence, and machine learning tasks: inference by Gibbs sampling of Poisson mixed models (algorithm, sampling of unobserved variables, Dirichlet distribution, gamma distribution, conditional distribution, categorical distribution, posterior distribution, simultaneous distribution, superparameter, knowledge model, latent variable) categorical distribution, posterior distribution, simultaneous distribution, hyperparameters, knowledge models, data generating processes, latent variables)

Ryotaro Shiba, Shotaro Ikenami and historical novels

Ryotaro Shiba, Shotaro Ikenami and historical novels (Ryosuke Kakine, Muromachi Muyori, Yoshinobu Kadoi, Ieyasu: Building Edo, Yuichi Shimpo, Shin Keian Taiheiki, Kokugoro Castle, Sho no Shield, Honobu Yonezawa, Shogo Imamura, 166th Naoki Prize, authentic mystery novel, Musashi Miyamoto, Eiji Yoshikawa, Kageyama Nakazato, Daibosatsu Pass, Onihei Hankacho, Sword for Swords, Umeyasu Fujie the Trap Man, Owl Castle, Cloud over the Hill, Ryoma Goes, Burning Sword, Kaido Yuku, Mountain Pass, 100th Birthday Anniversary)
中国古典:classics

The Analects of Confucius, a book of comprehensive “anthropology

Confucius' Analects: A Comprehensive Book of "Anthropology" (Communist Party, Chōkyū, Confucianism, Analects and Arithmetic, Shibusawa Eiichi, Loyalty, Filial Piety, Civility, Yushima Seido, Kodokan, Spring and Autumn Period)
アルゴリズム:Algorithms

Protected: Hedge Algorithm and Exp3 Measures in the Adversary Bandid Problem

Hedge algorithm and Exp3 measures in adversarial bandit problems utilized in digital transformation, artificial intelligence, and machine learning tasks pseudo-regret upper bound, expected cumulative reward, optimal parameters, expected regret, multi-armed bandit problem, Hedge Algorithm, Expert, Reward version of Hedge algorithm, Boosting, Freund, Chabile, Pseudo-Code, Online Learning, PAC Learning, Question Learning
アルゴリズム:Algorithms

Protected: Representation Theorems and Rademacher Complexity as the Basis for Kernel Methods in Statistical Mathematics Theory

Representation theorems and Rademacher complexity as a basis for kernel methods in statistical mathematics theory used in digital transformation, artificial intelligence, and machine learning tasks Gram matrices, hypothesis sets, discriminant bounds, overfitting, margin loss, discriminant functions, predictive semidefiniteness, universal kernels, the reproducing kernel Hilbert space, prediction discriminant error, L1 norm, Gaussian kernel, exponential kernel, binomial kernel, compact sets, empirical Rademacher complexity, Rademacher complexity, representation theorem
アルゴリズム:Algorithms

Protected: Batch Stochastic Optimization – Stochastic Variance-Reduced Gradient Descent and Stochastic Mean Gradient Methods

Batch stochastic optimization for digital transformation, artificial intelligence, and machine learning tasks - stochastic variance reduced gradient descent and stochastic mean gradient methods (SAGA, SAG, convergence rate, regularization term, strongly convex condition, improved stochastic mean gradient method, unbiased estimator, SVRG, algorithm, regularization, step size, memory efficiency, Nekaterov's acceleration method, mini-batch method, SDCA)
アルゴリズム:Algorithms

Protected: Gauss-Newton and natural gradient methods as continuous optimization for machine learning

Gauss-Newton and natural gradient methods as continuous machine learning optimization for digital transformation, artificial intelligence, and machine learning tasks Sherman-Morrison formula, one rank update, Fisher information matrix, regularity condition, estimation error, online learning, natural gradient method, Newton method, search direction, steepest descent method, statistical asymptotic theory, parameter space, geometric structure, Hesse matrix, positive definiteness, Hellinger distance, Schwarz inequality, Euclidean distance, statistics, Levenberg-Merkert method, Gauss-Newton method, Wolf condition
アルゴリズム:Algorithms

Protected: Approximate computation of various models in machine learning by Bayesian inference

Approximate computation of various models in machine learning using Bayesian inference for digital transformation, artificial intelligence, and machine learning tasks (structured variational inference, variational inference algorithms, mixture models, conjugate prior, KL divergence, ELBO, evidence lower bound, collapsed Gibbs sampling, blocking Gibbs sampling, approximate inference)
web技術:web technology

ISWC2022Papers

ISWC2022Papers From ISWC2022, an international conference on Semantic Web technologies, one of the artificial ...
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