Considerations for causal Inference and strong AI
Cause and effect cannot be derived from data alone
‘The Book of Why: The New Science of Cause and Ef...
ICT技術:ICT Technology
Overview of the policy gradient method and examples of algorithms and implementations
Overview of the policy gradient method
The Policy Gradient Method is one of the methods in Reinforcement Le...
Overview of R-GCN and examples of algorithms and implementations
Overview of R-GCN
R-GCN (Relational Graph Convolutional Network) is a type of neural network that performs...
Overview of negative sampling and examples of algorithms and implementations
Overview of negative sampling
Negative sampling is a learning algorithm in natural language processing ...
Diversity Promotion Ranking Overview, Algorithm and Implementation Examples
Diversity Promotion Ranking Overview
Diversity-Promoting Ranking is one of the methods that play an important ...
Statistical physics and its application to artificial intelligence technology
Statistical physics overview
Statistical physics is a branch of physics that studies the collective behaviour o...
Overview of HIN2Vec-PCA and examples of algorithms and implementations
Overview of HIN2Vec-PCA
HIN2Vec-PCA is a method that combines HIN2Vec and principal component analysis (PC...
Overview of mini-batch learning and examples of algorithms and implementations
Overview of mini-batch learning.
Minibatch learning is one of the most widely used and efficient learning me...
Overview of Maximum Marginal Relevance (MMR) and examples of algorithms and implementations
Overview of Maximum Marginal Relevance (MMR)
Maximum Marginal Relevance (MMR) is one of the ranking methods fo...
Web Reasoning and Rule Systems
Web Reasoning and Rule Systems
Web Reasoning and Rule Systems
This book is the refereed proceedings o...