Adaptive Model-Based Reinforcement Learning for Fast-Charging Optimization of Lithium-Ion Batteries.

Adaptive boosting with fairness-aware reweighting technique for fair classification.

Active learning with fairness-aware clustering for fair classification considering multiple sensitive attributes.

Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel.

Parallel Bayesian Optimization Using Satisficing Thompson Sampling for Time-Sensitive Black-Box Optimization.

Fast Charging of Lithium-Ion Batteries Using Deep Bayesian Optimization with Recurrent Neural Network.

Dynamic Bhattacharyya Bound-Based Approach for Fault Classification in Industrial Processes.

Constrained Bayesian Optimization for Minimum-Time Charging of Lithium-Ion Batteries.

Fault Detection in Industrial Systems Using Maximized Divergence Analysis Approach.

Fault Diagnosis in Industrial Processes by Maximizing Pairwise Kullback-Leibler Divergence.

Latent variable modeling approach for fault detection and identification of process correlations.

Maximized Mutual Information Analysis Based on Stochastic Representation for Process Monitoring.

Dynamic Minimax Probability Machine-Based Approach for Fault Diagnosis Using Pairwise Discriminate Analysis.

Locality preserving discriminative canonical variate analysis for fault diagnosis.

Simultaneous Identification of Bidirectional Path Models Based on Process Data.

A combined canonical variate analysis and Fisher discriminant analysis (CVA-FDA) approach for fault diagnosis.

Simultaneous identification of bi-directional paths in closed-loop systems with coloured noise.