グラフ理論 Machine Learning Professional Series – Gaussian Processes and Machine Learning Reading Notes
Summary
A Gaussian Process (GP) is a nonparametric regression and classification method based on probability th...
微分積分:Calculus
グラフ理論 グラフ理論 Machine Learning Startup Series – Introduction to Machine Learning with Bayesian Inference Reading Notes
Summary
Bayesian estimation can be one of the statistical methods for interpreting data and learning models fro...
グラフ理論 Nonparametric Bayesian and Gaussian Processes
Overview
Nonparametric Bayes is a method of Bayesian statistics, an "old and new technique" that was already theo...
ベイズ推定 Machine Learning with Bayesian Inference and Graphical Model
Machine Learning with Bayesian Inference and Graphical Model
Machine learning using Bayesian inference is a stati...
ベイズ推定 Variational Bayesian Learning
Variational Bayesian Learning
Variational Bayesian learning applies a variational approach to the probabilistic m...
ベイズ推定 Machine Learning Professional Series “Variational Bayesian Learning” reading notes
Summary
Variational Bayesian learning applies a variational approach to stochastic models in Bayesian estimatio...
オンライン学習 Protected: Combinatorial online prediction
Combinatorial, online prediction problems with a set of discrete structures as the decision space for digital transformation , artificial intelligence , and machine learning task utilization.
オンライン学習 Protected: Online prediction based on randomness
Randomness-based FPL(Follow the Perturbed Leader) Strategy and Gumbel Distribution for Improving Online Predictive Performance for Digital Transformation , Artificial Intelligence and Machine Learning Tasks
オンライン学習 Protected: Online convex optimization (3) exp concavity and ONS
Convex optimization for online prediction for digital transformation , artificial intelligence , and machine learning tasks (the case of exp concavity and ONS).
オンライン学習 Protected: Online Convex Optimization (2) Complementing FTL Strategies with Regularization
Complementing the FTL strategy by introducing regularization techniques (L2 norm) in online prediction for digital transformation , artificial intelligence , and machine learning tasks.