数学:Mathematics

Decision Theory and Mathematical Decision Making Techniques

We will discuss mathematical decision-making techniques used in reinforcement learning, online prediction, and algorithms for high-speed automated stock trading. After describing the four decision strategies, I will introduce subjective probability, Bayesian theory, multiple concept theory, and supply rise theory.

2021.06.05

数学:Mathematics確率・統計:Probability and Statistics

Protected: Matrix Decomposition -Extraction of relational features between two objects

Extraction of relationships by machine learning, matrix factorization approach, non-negative matrix factorization

2021.05.30

機械学習:Machine Learning線形代数:Linear Algebra

Protected: Clustering Techniques for Asymmetric Relational Data – Probabilistic Block Model and Infinite Relational Model

Machine Learning Extraction of Relationships, Probabilistic Block Model and Infinite Relation Model

2021.05.29

機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: Clustering of symmetric relational data – Spectral clustering

Extraction of relationships, knowledge extraction and prediction, spectral clustering by machine learning for graph analysis, etc.

2021.05.28

最適化:Optimization検索技術:Search Technology機械学習:Machine Learning線形代数:Linear Algebra

Protected: Variational Bayesian Learning Introduction

Fundamentals of Variational Methods for Optimizing Bayesian Estimation in Machine Learning

2021.05.27

アルゴリズム:Algorithms機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: Online Machine Learning Overview

Basics of online learning for sequential learning from a small number of supervised data

2021.05.26

アルゴリズム:Algorithms最適化:Optimization機械学習:Machine Learning

Protected: Bayesian Deep Learning – Introduction

Overview of Bayesian deep models, an evolution of deep learning and probabilistic generative models.

2021.05.25

アルゴリズム:Algorithms機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics

Protected: Graphical Model Overview and Bayesian Network

Graphical model overview for efficient approach to stochastic generative models, Bayesian networks

2021.05.24

推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing

Protected: Graphical Models Overview and Markov Probability Fields

Graphical model overview for efficient approach to stochastic generative models, Markov stochastic processes

2021.05.23

推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: An overview of the expert integration problem in online forecasting and its implementation in Regret

Overview of online predictive learning for solving sequential prediction problems, introduction to Regret

2021.05.22

推論技術:inference Technology最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics