algorithm

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)

2023.01.25

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集合論:Set theory

Generative Art, Programs and Algorithms

Generative Art and Programs and Algorithms (clojurescript, javascript, compilation, quil templates, python mode, java mode, processing, ArtBlock, blockchain, curation, ken rilando, autopoiesis, robots, teamlab, algorithms, art, Clojure/Conj, complex systems, information theory, mathematics)

2023.01.02

アート:Artテクノロジー:Technologyビジネス:Business

Protected: Analysis of time series data using Clojure

Analysis of time series data such as AR, MA, ARMA, etc. using Clojure for digital transformation, artificial intelligence machine learning tasks ACF, PACF, Partial Autocorrelation, Durbin-Levinson algorithm, autocovariance, moving average models, autocorrelation models, hybrid, random walk, discrete-time models

2022.10.18

Clojureアルゴリズム:Algorithms微分積分:Calculus時系列データ解析最適化: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

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

Theory and Algorithms for the Bandit Problem

The theory and algorithms of the Bandit Problem for selecting optimal strategies to be utilized in digital transformation, artificial intelligence, and machine learning tasks

2022.08.11

バンディッド問題強化学習

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

Protected: Support vector machine software and implementation

Classification and regression with SVM using R kernlab in support vector machines used for digital transformation, artificial intelligence and machine learning tasks and LIBSVM algorithms SMO algorithm, shrinking

2022.07.29

アルゴリズム:Algorithms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関係データ学習音声信号認識技術

Protected: Partitioning Methods in Support Vector Machines (2) DCDM Algorithm for Linear SVM

DCDM algorithm (dual coordinate descent method algorithm), an efficient algorithm for processing large amounts of (sparse) data on support vector machines (algorithm for linear SVM used in LIBLINEAR) used in digital transformation (DX), artificial intelligence (AI) and machine learning (ML) tasks.

2022.07.01

アルゴリズム:Algorithmsグラフ理論微分積分:Calculus時系列データ解析最適化: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自然言語処理:Natural Language Processing

Protected: Fundamentals of Submodular Optimization (4) Approaches by Linear Optimization and Norm Optimization on a Fundamental Polyhedron

Submodular approach by linear optimization and norm optimization on a base polyhedron in submodular optimization, one of the optimization methods for discrete information used in digital transformation, artificial intelligence, and machine learning tasks.

2022.04.20

IOT技術:IOT Technologyアルゴリズム:Algorithmsグラフ理論幾何学:Geometry推論技術:inference Technology数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning関係データ学習

Protected: Fundamentals of Submodular Optimization (1) Definition and Examples of Submodular Functions

Submodular functions (cover functions, graph cut functions, concave functions) and optimization as a basis for discrete information optimization algorithms for digital transformation, artificial intelligence, and machine learning tasks

2022.04.13

Symbolic Logicアルゴリズム:Algorithmsグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習