微分積分:Calculus

Protected: Fundamentals of Submodular Optimization (3)Algorithm for Submodular Function Minimization Problem Using the Minimum Norm Point of the Fundamental Polyhedron

Algorithm for a submodular function minimization problem using base polyhedral minimum norm points, one of the methods of optimization methods (submodular optimization) for discrete information used in digital transformation, artificial intelligence, and machine learning tasks.

2022.04.15

Symbolic Logicアルゴリズム:Algorithmsグラフ理論微分積分:Calculus推論技術:inference Technology数理論理学最適化:Optimization確率・統計:Probability and Statistics関係データ学習

Iwanami Data Science – The World of Bayesian Modeling Reading Notes

Iwanami Data Science - The World of Bayesian Modeling Reading Notes Memo for reading "Iwanami Data Science: Th...

2022.04.03

ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

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...

2022.03.27

グラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習

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...

2022.03.20

グラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

Nonparametric Bayesian and Gaussian Processes

Overview Nonparametric Bayes is a method of Bayesian statistics, an "old and new technique" that was already theo...

2022.03.16

グラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習

Machine Learning with Bayesian Inference and Graphical Model

Machine Learning with Bayesian Inference and Graphical Model Machine learning using Bayesian inference is a stati...

2022.03.16

ベイズ推定微分積分:Calculus最適化:Optimization確率・統計:Probability and Statistics自然言語処理:Natural Language Processing

Variational Bayesian Learning

Variational Bayesian Learning Variational Bayesian learning applies a variational approach to the probabilistic m...

2022.03.13

ベイズ推定微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

Machine Learning Professional Series “Variational Bayesian Learning” reading notes

Summary Variational Bayesian learning applies a variational approach to stochastic models in Bayesian estimatio...

2022.03.13

ベイズ推定微分積分:Calculus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: 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.

2022.02.15

オンライン学習幾何学:Geometry強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

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

2022.02.14

オンライン学習幾何学:Geometry強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics