音声信号認識技術

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: Model Selection and Regularized Path Tracking (2)Regularized Path Tracking

On Regularized Path Tracking Algorithms in Model Validation for Improving Efficiency of SVMs Used in Digital Transformation, Artificial Intelligence , and Machine Learning Tasks

2022.07.15

アルゴリズム:Algorithms微分積分:Calculus最適化:Optimization機械学習:Machine Learning画像認識技術音声信号認識技術

Protected: Partitioning Method on Support Vector Machines (1) SMO Algorithm

Efficiency using the partitioning method (SMO algorithm) on support vector machines utilized for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks

2022.06.24

アルゴリズム:Algorithmsグラフ理論微分積分:Calculus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: 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: 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: 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

Machine Learning Professional Series – Relational Data Learning Post-Reading Notes

Overview of relational data learning to extract the meaning and knowledge behind information used in digital transformation , artificial intelligence , and machine learning tasks.

2021.12.03

地理空間情報処理推論技術:inference Technology機械学習:Machine Learning画像認識技術自然言語処理:Natural Language Processing音声信号認識技術

Protected: Evolving Deep Learning with PyTorch(OpenPose, SSD, AnoGAN, Efficient GAN, DCGAN, Self-Attention GAN, BERT, Transformer, GAN, PSPNet, 3DCNN, ECO)

OpenPose, SSD, AnoGAN, Efficient GAN, DCGAN, Self-Attention GAN, BERT, Transformer, GAN using pytorch for Digital Transformation and Artificial Intelligence tasks, PSPNet,3DCNN,ECO and other advanced DNNs

2021.11.14

python機械学習:Machine Learning深層学習:Deep Learning画像認識技術自然言語処理:Natural Language Processing音声信号認識技術

Protected: Applying Deep Learning to Speech Recognition

Overview of neural network applications (TDNN, RNN, CNN) and deep learning applications (LSTM, CTC) for speech recognition technology used in digital transformation and artificial intelligence tasks

2021.10.07

機械学習:Machine Learning深層学習:Deep Learning音声信号認識技術