最適化:Optimization

Protected: Implementation of particle filter on time series data

Data assimilation using particle filters for time series data analysis utilized in digital transformation, artificial intelligence, and machine learning tasks and comparison of Kalman filter, particle filter (sequential Monte Carlo), and Markov chain Monte Carlo (MCMC) methods

2022.06.22

IOT技術:IOT TechnologyRStream Data Processing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

Protected: Introduction to Optimization with Support Vector Machines: Optimality Conditions and Generic Solution Methods

Optimality conditions (strong duality and KKT) and generic solution methods (active set and interior point method) in support vector machines used for digital transformation, artificial intelligence and machine learning tasks

2022.06.17

Symbolic Logicアルゴリズム:Algorithmsスパースモデリング最適化:Optimization機械学習:Machine Learning画像認識技術確率・統計:Probability and Statistics自然言語処理:Natural Language Processing音声信号認識技術

Protected: State Space Modeling with R – using dlm and KFAS (3) Analysis with KFAS

Time series data analysis for digital transformation, artificial intelligence, and machine learning tasks; examples of time series analysis on real data using KFAS in R normal distribution, Poisson distribution, Kalman filter, first-order difference model, second-order difference model

2022.06.16

IOT技術:IOT TechnologyRStream Data Processing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

Dream of a realistic SimCity

Integration of simulation and machine learning technologies used for digital transformation, artificial intelligence, and machine learning tasks; application of SimCity to the real world using emulation and machine learning

2022.06.15

アルゴリズム:Algorithmsグラフ理論コンピューターシミュレーション微分積分: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

Machine Learning Professional Series Probabilistic Optimization Reading Notes

Summary Stochastic optimization in machine learning will refer to the solution of optimization problems using r...

2022.06.11

微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: kernel function

General kernel functions in support vector machines used in digital transformation (DX), artificial intelligence (AI), and machine learning, and kernel functions on probabilistic, string, and graph-type data

2022.06.10

アルゴリズム:Algorithmsグラフ理論微分積分:Calculus推論技術:inference Technology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音声信号認識技術

Protected: State space modeling with R – using dlm and KFAS (2) Seasonal adjustment model with dlm

Analysis of time series data used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks, and seasonal-variant time series models on real data using R's dlm

2022.06.09

RStream Data Processingアルゴリズム:Algorithms微分積分:Calculus推論技術:inference Technology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非同期/並行処理:Asynchronous/parallel processing

Shaky Proteins and Old Me: Data Science in the Age of Misfolding

Integration of simulation and machine learning technologies used in digital transformation, artificial intelligence and machine learningtasks; application of simulation and machine learning PCA, RMA, canonical correlation analysis, independent component analysis, Bayesian inference, hidden Markov models) to protein functional analysis (misfolding, etc.

2022.06.08

IOT技術:IOT TechnologyStream Data Processingシミュレーション地理空間情報処理微分積分:Calculus推論技術:inference Technology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

Machine Learning Professional Series Statistical Learning Theory Reading Notes

Summary The theory of statistical properties of machine learning algorithms can be used to theoretically elucid...

2022.06.04

ベイズ推定微分積分: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

Protected: Support vector machines for unsupervised learning

Application of support vector machines for digital transformation, artificial intelligence, and machine learning tasks (1-class SVM with nu-SV classification algorithm for unsupervised classification used for anomaly detection)

2022.06.03

アルゴリズム:Algorithmsグラフ理論微分積分:Calculus数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning画像認識技術確率・統計:Probability and Statistics自然言語処理:Natural Language Processing