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...
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)
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
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
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
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
Protected: Unsupervised Learning with Gaussian Processes (1)Overview and Algorithm of Gaussian Process Latent Variable Models
Overview and algorithms of unsupervised learning using Gaussian Process Latent Variable Models GPLVM, an application of probabilistic generative models used in digital transformation, artificial intelligence, and machine learning, Bayesian Gaussian Process Latent Variable Models ,Bayesian GPLVM
On the Road: Travel and History of Awa and Awaji Island
Ryotaro Shiba's Kaido Yuku: Travels and History of Awa and Awaji Island (Awa Odori Dance, Pilgrimage, 88 Places on Shikoku Island, Kobo Daishi, Kukai, Awa Ai, German Pavilion, World War I, POWs, Tenjirushi, Doura, Naruto, Whirlpool, Naruto Bridge, Zenbo Yasunori, Nijigen no Mori, Akashi Kaikyo Bridge)
Read “Augustine” Confessions at the Heart of Christianity
Read Augustine's "Confessions" at the heart of Christianity (traveler, theology, philosophy, interminable trials, chance and necessity, self, mystery, Hortensius experience, biblical experience, Manichaeism, conversion, little man, Cicero, Hortensius, free will theory, Martin Heidegger, existence and time, Hannah Arendt, Augustine's concept of love, Roman Empire, Carthage)
Installation and operation of Apache server and LAMP
Installation and operation of Apache server and LAMP (MariaDB, PHP, CentOS, Mac, Windows) utilized for digital transformation (DX), artificial intelligence (AI) and machine learning (ML) tasks