April 2022 | Page 2 | Deus Ex Machina

Protected: Maximization of submodular functions and application of the greedy method (1) Overview of the greedy method and its application to document summarization

Optimization methods for discrete information used in digital transformation, artificial intelligence, and machine learning tasks: application of greedy methods to undermodular function maximization and its use in document summarization tasks

2022.04.22

IOT技術:IOT Technologyアルゴリズム:Algorithms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確率・統計:Probability and Statistics関係データ学習

Data Stream Processing Architecture (DSMS)

Machine learning and system architecture of data streams (time series data) used for cross-fusion IOT utilization, and data stream management system: DSMS (Data Stream Management System)

2022.04.21

IOT技術:IOT TechnologyStream Data Processingセマンテックウェブ技術:Semantic web Technology推論技術:inference Technology検索技術:Search Technology機械学習:Machine Learning

Protected: Fundamentals of Submodular Optimization (5) Lovász Extension and Multiple Linear Extension

Interpretation of submodularity using Lovász extensions and multiple linear extensions as a basis for submodular optimization, an approach to discrete information used in digital transformation, artificial intelligence, and machine learning tasks

2022.04.21

アルゴリズム:Algorithmsグラフ理論スパースモデリング微分積分:Calculus推論技術:inference Technology数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning

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: PF for fast processing of streamed data and large amounts of data: Apache Spark Overview

Overview of ApacheSpark, an open source platform used for digital transformation, artificial intelligence, and machine learning tasks to process streamed and massive data at high speed

2022.04.19

Stream Data Processingweb技術:web technologyオンライン学習強化学習時系列データ解析機械学習:Machine Learning異常検知・変化検知非同期/並行処理:Asynchronous/parallel processing

Protected: Web page development using Laravel (2) up to building a simple application

Example of building a simple web app in Laravel, a PHP framework used for digital transformation, artificial intelligence, and machine learning tasks

2022.04.18

CSSjavascriptPHPweb技術: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

Knowledge Graph and Semantic Computing

Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...

2022.04.17

Symbolic Logicグラフ理論セマンテックウェブ技術:Semantic web 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推論技術:inference Technology検索技術:Search Technology自然言語処理:Natural Language Processing関係データ学習

Inductive logic Programming 2018

Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...

2022.04.16

Symbolic Logic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

Protected: Fundamentals of Submodular Optimization (3)Algorithm for Submodular Function Minimization Problem Using the Minimum Norm Point of the Fundamental Polyhedron

Algorithm for a submodular function minimization problem using base polyhedral minimum norm points, one of the methods of optimization methods (submodular optimization) for discrete information used in digital transformation, artificial intelligence, and machine learning tasks.

2022.04.15

Symbolic Logicアルゴリズム:Algorithmsグラフ理論微分積分:Calculus推論技術:inference Technology数理論理学最適化:Optimization確率・統計:Probability and Statistics関係データ学習

Protected: Fundamentals of Submodular Optimization (2) Basic Properties of Submodular Functions

Three basic properties of submodular functions (normalized, non-negative, symmetric) as a basis for optimization algorithms (submodular optimization) of discrete information for digital transformation, artificial intelligence and machine learning tasks and their application to graph cut maximization and minimization problems

2022.04.14