ML

推論技術:inference Technology

Protected: Fundamentals of statistical causal inference (1) – Definition of causality by counterfactual model and structural equation model

Foundations of Statistical Causal Inference for Digital Transformation , Artificial Intelligence and Machine Learning Tasks: Defining Causality in Counterfactual Models and Structural Equation Models
Symbolic Logic

Graph data processing algorithms and their application to Machine Learning and Artificial Intelligence tasks

Theory, implementation, and use of algorithms for analyzing graph data.
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.
オンライン学習

Protected: Online Convex Optimization(1) FTL strategy and BTL supplement

Online Convex Optimization and FTL Strategies with Online Prediction for Digital Transformation , Artificial Intelligence , and Machine Learning Tasks with BTL Supplement
オンライン学習

Protected: New Developments in Reinforcement Learning (2) – Approaches Using Deep Learning

On seven methods for improving deep reinforcement learning used in digital transformation , artificial intelligence , and machine learning tasks (first generation DQN, dual Q learning (dual DQN method), prioritized experience replay, collision Q networks, distributed reinforcement learning (categorical DQN method) noise networks, n-step cutting returns) and alpha zero
オンライン学習

Protected: New Developments in Reinforcement Learning (1) – Reinforcement Learning with Risk Indicators

Different approaches (regular process TD learning, RDPS methods) and implementations (Monte Carlo, analytical methods) in risk-aware reinforcement learning methods for digital transformation , artificial intelligence , and machine learning tasks.
オンライン学習

Protected: Partially Observed Markov Decision Processes (2) Planning POMDPs

Reinforcement learning for digital transformation , artificial intelligence , and machine learning tasks; obtaining optimal strategies using partial observation Markov decision process planning methods.
タイトルとURLをコピーしました