アーキテクチャ

AWS Cloud Service Design Patterns (3)

AWS Cloud Service Design Patterns utilized for Digital Transformation, Artificial Intelligence, and Machine Learning tasks (Operations and Maintenance Patterns, Bootstrap, Cloud DI, Stack Development, Server Swapping, Monitoring Integration, Weighted Transition, Log Aggregation, Ondemand Activation, Network Patterns, Backnet, Functional Firewall, and Operational Activation). Monitoring Integration, Weighted Transition, Log Aggregation, Ondemand Activation, Network Patterns, Backnet, Functional Firewall, Operational Firewall, Multi Load Balancer, WAF Proxy, CloudHub, Sorry Page, Self Registration, RDP Proxy, Floating Gateway, Shared Service, High Availability NAT)
2023.02.14
アーキテクチャコンピューターネットワーク技術
web技術:web technology

Protected: On cloud-native and service-centric development

On cloud-native and service-centric development leveraged for digital transformation, artificial intelligence, and machine learning tasks inter-organizational, siloed, KPIs, business value, Conway's Law, organizational restructuring, process reform, CNCF Incubating Stage, CNCF Graduate Stage, CNCF Sandbox Stage, Technical Oversight Committee, End User Advisory Board, Cloud Native Application Development, Kubernetes Application Modernization, The Twelve-Factor App, 12 Application Principles, Container Orchestration, APIs, Service Based Architecture, SOA, Service Oriented Architecture, Microservices, Sparse Coupling, Delivery Performance, MTTR, Lead Time, Change Loss Rate, Deployment Frequency, Docker
2023.02.13
web技術:web technologyアーキテクチャコンピューターマルチエージェントシステムユーザーインターフェース/データビジュアライゼーション
ICT技術:ICT Technology

Theory, Mathematics and Algorithms for Artificial Intelligence Technology

Theory and basic algorithms of artificial intelligence techniques (metaheuristics, graph algorithms, dynamic programming, sphere theory, logic, mathematics) used in digital transformation, artificial intelligence and machine learning tasks.
2023.02.12
ICT技術:ICT Technologylife tips人工知能:Artificial Intelligence
ICT技術:ICT Technology

Artificial Intelligence Technology

Artificial Intelligence technologies used for Digital Transformation (DX), Artificial Intelligence (AI) and Machine Learning (ML) tasks
2023.02.12
ICT技術:ICT Technologylife tips人工知能:Artificial Intelligence
中国古典:classics

The Thought of Zhuangzi: How the Mind Can Be Free

The Thought of Zhuangzi: How the Mind Can Be Free (Qimoten, Delusion, Delusion of Hearing, Irreconcilable Character, Zen, The Human World Arc, O Teio Arc, Tokujinshi Arc, Anti-Common Sense, Saigyo Hoshi, Kamo Chomei, Matsuo Basho, Sengai Yoshihon, Ryokan, Yukawa Hideki, O Teio Arc, The Seven Bones of Chaos, Novel, Zhuang Zhou)
2023.02.11
中国古典:classics哲学:philosophy禅:Zen課題解決:Problem solving
アルゴリズム:Algorithms

Protected: Exp3.P measures and lower bounds for the adversarial multi-armed bandit problem Theoretical overview

Theoretical overview of Exp3.P measures and lower bounds for adversarial multi-arm bandit problems utilized in digital transformation, artificial intelligence, and machine learning tasks cumulative reward, Poly INF measures, algorithms, Arbel-Ruffini theorem, pseudo-riglet upper bounds for Poly INF measures, closed-form expressions, continuous differentiable functions, Audibert, Bubeck, INF measures, pseudo-riglet upper bounds for INF measures, random choice algorithms, optimal order measures, highly probable riglet upper bounds) closed form, continuous differentiable functions, Audibert, Bubeck, INF measures, pseudo-riglet lower bounds, random choice algorithms, measures of optimal order, highly probable riglet upper bounds
2023.02.10
アルゴリズム:Algorithmsオンライン学習スパースモデリングバンディッド問題幾何学:Geometry強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
アルゴリズム:Algorithms

Protected: Overview of C-Support Vector Machines by Statistical Mathematics Theory

Support vector machines based on statistical mathematics theory used in digital transformation, artificial intelligence, and machine learning tasks C-support vector machines (support vector ratio, Markov's inequality, probability inequality, prediction discriminant error, one-out-of-two cross checking method, LOOCV, the discriminant, complementarity condition, main problem, dual problem, optimal solution, first order convex optimization problem, discriminant boundary, discriminant function, Lagrangian function, limit condition, Slater constraint assumption, minimax theorem, Gram matrix, hinge loss, margin loss, convex function, Bayes error, regularization parameter)
2023.02.09
アルゴリズム:Algorithmsスパースモデリング幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
アルゴリズム:Algorithms

Protected: Distributed processing of on-line stochastic optimization

Distributed online stochastic optimization for digital transformation, artificial intelligence, and machine learning tasks (expected error, step size, epoch, strongly convex expected error, SGD, Lipschitz continuous, gamma-smooth, alpha-strongly convex, Hogwild!), parallelization, label propagation method, propagation on graphs, sparse feature vectors, asynchronous distributed SGD, mini-batch methods, stochastic optimization methods, variance of gradients, unbiased estimators, SVRG, mini-batch parallelization of gradient methods, Nesterov's acceleration method, parallelized SGD)
2023.02.08
アルゴリズム:Algorithmsグラフ理論スパースモデリング幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory
アルゴリズム:Algorithms

Protected: Conjugate gradient and nonlinear conjugate gradient methods as continuous optimization in machine learning

Conjugate gradient methods as continuous machine learning optimization for digital transformation, artificial intelligence, and machine learning tasks (moment method, nonlinear conjugate gradient method, search direction, inertia term, Polak-Ribiere method, linear search, Wolf condition, Dai-Yuan method, strong Wolf condition, Fletcher-Reeves method, global convergence, Newton method, rapid descent method, Hesse matrix, convex quadratic function, conjugate gradient method, minimum eigenvalue, maximum eigenvalue, affine subspace, conjugate direction method, coordinate descent method)
2023.02.07
アルゴリズム:Algorithms幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
アルゴリズム:Algorithms

Protected: Theory of Noisy L1-Norm Minimization as Machine Learning Based on Sparsity (2)

Theory of noisy L1 norm minimization as machine learning based on sparsity for digital transformation, artificial intelligence, and machine learning tasks numerical examples, heat maps, artificial data, restricted strongly convex, restricted isometric, k-sparse vector, norm independence, subdifferentiation, convex function, regression coefficient vector, orthogonal complementary space
2023.02.06
アルゴリズム:Algorithmsスパースモデリング幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
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