2022-11

IOT技術:IOT Technology

Brain-machine interface utilization and OpenBCI

Brain Machine Interface applications and OpenBCI (Galea, VR, steam deck, Valve, Steam, EEG, EOG, EMG, EDA, PPG, Panatronix, UX, meditation, stress, Shimadzu, NIRS, rehabilitation, exoskeletal robots, and BMI neurorehabilitation, Blackrock Microsystems, LLC, functional compensatory, functional restorative, non-invasive, fMRI, invasive, magnetic brain field measurement, near infrared photometry, NIRD, EEG, EEG sensor, prosthetic hand)
2022.11.30
IOT技術:IOT TechnologyStream Data Processingコンピューターハードウェア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
アルゴリズム:Algorithms

Implementation of Neural Networks and Error Back Propagation using Clojure

Implementation of neural nets and error back propagation using Clojure for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks
2022.11.29
アルゴリズム:Algorithms微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
Clojure

Use of ElasticStash for monitoring system operations, including microservices

Leveraging ElasticStash for system operations monitoring, including microservices leveraged for digital transformation artificial intelligence, and machine learning tasks Riemann, rollup, throttle structure, KafKa plugin, UTC, timbre LogStash, log4j, tools.logging, structured logging, common log formats, visualization features, dashboards, Kibana, pipeline, UDP, Collectd, RRD, stdin, stdout, ELK Stack, Elastic Stack Apache Kafka
2022.11.28
Clojureアーキテクチャコンピューターセキュリティデータベース技術:DataBase Technologyマルチエージェントシステム
情報理論/計算理論

Information Theory Math & Science Reading Notes

Machine Learning Technology.  Artificial Intelligence Technology   Digital Transformation Technology  Natural Language P...
2022.11.27
情報理論/計算理論
コンピューター

KI 2019: Advances in Artificial Intelligence Papers

KI2019 In the previous article, we discussed KI 2018. In this issue, we describe the 42nd German Con...
2022.11.27
コンピューター人工知能:Artificial Intelligence
アルゴリズム:Algorithms

Protected: Information Geometry of Positive Definite Matrices (2) From Gaussian Graphical Models to Convex Optimization

Information geometry of positive definite matrices utilized in digital transformation, artificial intelligence, and machine learning tasks From Gaussian graphical models to convex optimization (chordal graphs, triangulation graphs, dual coordinates, Pythagorean theorem, information geometry, geodesics, sample variance-covariance matrix, maximum likelihood Estimation, divergence, knot space, Riemannian metric, multivariate Gaussian distribution, Kullback-Leibler information measure, dual connection, Euclidean geometry, narrowly convex functions, free energy)
2022.11.26
アルゴリズム:Algorithmsグラフ理論幾何学: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: Measures for Stochastic Bandid Problems -Theoretical Limitations and the ε-Greedy Method

Theoretical limits and ε-greedy method, UCB method, riglet lower bounds for consistent measures, and KL divergence as measures for stochastic banded problems utilized in digital transformation , artificial intelligence , and machine learning tasks
2022.11.25
アルゴリズム:Algorithmsバンディッド問題強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra
微分積分:Calculus

Protected: Complexity of Hypothesis Sets in Statistical Mathematics Theory

Complexity of sets of hypotheses in statistical mathematical theory used in digital transformation, artificial intelligence, and machine learning tasks Rademacher complexity, VC dimension, large number factor, law of large uniform numbers, decision stocks, set of linear discriminators, set of linear functions, Cauchy-Schwartz inequality, Jensen inequality, Masar's complement, Talagrande's complement, empirical Rademacher complexity, Sauer's complement, Radon's theorem
2022.11.24
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: Stochastic Optimization and Online Optimization Overview

Stochastic and online optimization used in digital transformation, artificial intelligence, and machine learning tasks expected error, riglet, minimax optimal, strongly convex loss function, stochastic gradient descent, stochastic dual averaging method, AdaGrad, online stochastic optimization, batch stochastic optimization
2022.11.23
アルゴリズム:Algorithms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: Unconstrained optimization for continuous optimization in machine learning

Unconstrained Optimization for Continuous Optimization in Machine Learning for Digital Transformation, Artificial Intelligence, and Machine Learning tasks machine epsilon, stopping conditions without scaling, stopping conditions with scaling, Taylor's theorem, stopping conditions for optimization algorithms, Hesse matrix
2022.11.22
アルゴリズム:Algorithms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
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