オンライン学習

オンライン学習

Protected: Planning Problems (2) Implementation of Dynamic Programming (Value Iterative Method and Measure Iterative Method)

Implementation of Dynamic Programming (Value Iteration and Policy Iteration) for Planning Problems as Reinforcement Learning for Digital Transformation , Artificial Intelligence and Machine Learning Tasks
オンライン学習

Protected: Evaluating the performance of online learning(Perceptron, Regret Analysis, FTL, RFTL)

Perceptron and Riglet Analysis (FTL, RFTL) for evaluating online learning used for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習

Protected: Advanced online learning (4) Application to deep learning (AdaGrad, RMSprop, ADADELTA, vSGD)

Application to online learning in AdaGrad, RMSprop, and vSGD used for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習

Protected: Advanced online learning (3) Application to deep learning (mini-batch stochastic gradient descent, momentum method, accelerated gradient method)

Improving computational efficiency by applying mini-batch stochastic gradient descent, momentum, and accelerated gradient methods to deep learning for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習

Protected: Advanced Online Learning (2) Distributed Parallel Processing(Parallelized mini-batch stochastic gradient method, IPM, BSP, SSP)

Distributed parallel processing of online learning (parallelized mini-batch stochastic gradient method, IPM, BSP, SSP) to efficiently process large scale data for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習

Machine Learning Professional Series “Online Prediction” Reading Memo

Online prediction, which is machine learning that combines prediction and decision making problems used in digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習

Protected: Advanced online learning (1) High accuracy Approach (Perceptron, PA, PA-I, PA-II, CW, AROW, SCW)

Introduction to various methods for improving the accuracy of online learning for digital transformation , artificial intelligence and machine learning tasks (Perceptron, PA, CW, AROW, SCW)
オンライン学習

Protected: Fundamentals of Online Learning Stochastic Gradient Descent – Application to Perceptron, SVM, and Logistic Regression

Online learning applications to the perceptron, SVM, and logistic regression for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習

Online learning and online prediction

Online learning is a sequential machine learning technique used in digital transformation , artificial intelligence , and machine learning tasks, and online prediction combines these techniques with decision-making problems.
オンライン学習

Protected: Implementation in online learning – sparse vector computation and averaging perceptron, averaged stochastic gradient descent, lazy update

Various implementation techniques for online learning for digital transformation , artificial intelligence and machine learning tasks (sparse vector computation and averaging perceptrons, averaged stochastic gradient descent, lazy update).
タイトルとURLをコピーしました