機械学習:Machine Learning

Explainable Machine Learning

In the first half of Molnar's paper on Explainable Artificial Intelligence, he outlines that explanations can be intrinsic or post-hoc, and in the latter approach, an algorithm is used to construct an explanation from input-output pairs. A good explanation is one that can be compared with counterexamples.

2021.06.25

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

one hot vector and category vector with Clojure

Implementation of one-hot-vector and category-vector in Clojure for machine learning applications in natural language processing

2021.06.15

Clojure機械学習:Machine Learning自然言語処理:Natural Language Processing

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