幾何学:Geometry

アルゴリズム:Algorithms

Protected: Measures for Stochastic Banded Problems Likelihood-based measures (UCB and MED measures)

Measures for Stochastic Banded Problems Likelihood-based UCB and MED measures (Indexed Maximum Empirical Divergence policy, KL-UCB measures, DMED measures, Riglet upper bound, Bernoulli distribution, Large Deviation Principle, Deterministic Minimum Empirical Divergence policy, Newton's method, KL divergence, Binsker's inequality, Heffding's inequality, Chernoff-Heffding inequality, Upper Confidence Bound)
2022.12.09
アルゴリズム:Algorithmsバンディッド問題幾何学: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: 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: Implementation of model-free reinforcement learning in python (1) epsilon-greedy method

Implementation in python of the epsilon-Greedy method, a model-free reinforcement learning method for use in digital transformation, artificial intelligence, and machine learning tasks, multi-armed bandit
2022.11.03
アルゴリズム:Algorithmsマルチエージェントシステム幾何学:Geometry強化学習最適化: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: Replica Exchange Monte Carlo and Multicanonical Methods

On replica exchange Monte Carlo and multi-canonical methods, which are algorithms to avoid falling into local solutions in Markov chain Monte Carlo methods used for digital transformation, artificial intelligence, and machine learning tasks.
2022.09.18
アルゴリズム:Algorithmsグラフ理論ベイズ推定幾何学:Geometry微分積分:Calculus数理論理学:Mathematical logic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
R

Protected: Structured Support Vector Machines

SVM structure learning and parsing using the deletion plane method algorithm on support vector machines utilized for digital transformation, artificial intelligence, and machine learning tasks, and protein similarity sequence search
2022.08.08
R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画像認識技術異常検知・変化検知確率・統計:Probability and Statistics線形代数:Linear Algebra自然言語処理:Natural Language Processing音声信号認識技術
アルゴリズム:Algorithms

Protected: Overview of Stochastic Generative Models and Learning

Probabilistic generative models used in digital transformation , artificial intelligence and machine learning , overview of graphical models and maximum likelihood methods, MAP estimation, Bayesian estimation and Gibbs sampling.
2022.07.12
アルゴリズム:Algorithmsベイズ推定幾何学: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
幾何学:Geometry

Nine Stories of Probability and Statistics That Changed Humans and Society Reading Notes

Nine Stories of Probability and Statistics That Changed Humans and Society Reading Notes From Nine Stories of Pr...
2022.07.02
幾何学:Geometry微分積分:Calculus確率・統計:Probability and Statistics線形代数:Linear Algebra
アルゴリズム:Algorithms

Protected: Regression Analysis with Support Vector Machines (2) Approach to Nonlinear Regression Problems

Approaches to nonlinear regression problems with support vector machines (quantile regression, kernel quantile regression, heterogeneous distribution models, ε-insensitive loss functions) utilized in digital transformation, artificial intelligence, and machine learning tasks.
2022.05.27
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画像認識技術自然言語処理:Natural Language Processing関係データ学習音声信号認識技術
Symbolic Logic

Knowledge Graphs and Big Data Processing

Machine Learning Technology  Artificial Intelligence Technology  Natural Language Processing Technology  Semantic Web Te...
2022.05.08
Symbolic Logicweb技術:web technologyグラフ理論セマンテックウェブ技術:Semantic web Technologyデータベース技術:DataBase Technology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幾何学:Geometry推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
Symbolic Logic

Protected: Maximum Flow and Graph Cut (3) Inference and Graph Cut in Markov Stochastic Fields

Inference and graph cuts in Markov stochastic fields for graph maximal flow extraction by undermodular optimization, a discrete information optimization method for digital transformation, artificial intelligence, and machine learning tasks
2022.05.04
Symbolic Logicアルゴリズム:Algorithmsグラフ理論幾何学:Geometry微分積分:Calculus推論技術:inference Technology数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
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