Results 101 to 110 of about 741,105 (343)
CORR Synthesis: Can Decision Tree Learning Advance Orthopaedic Surgery Research? [PDF]
Clin Orthop Relat Res, 2023 Wilson A.
europepmc +1 more source
, 2019 Tactical decision making for autonomous driving is challenging due to the diversity of environments, the uncertainty in the sensor information, and the complex interaction with other road users.
Driggs-Campbell, Katherine +4 more
core +1 more source
Advanced Functional Materials, EarlyView.This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak +14 more
wiley +1 more source
Decision tree learning in Neo4j on homogeneous and unconnected graph nodes from biological and clinical datasets. [PDF]
BMC Med Inform Decis Mak, 2023 Mondal R +7 more
europepmc +1 more source
Verifiable Reinforcement Learning via Policy Extraction
, 2019 While deep reinforcement learning has successfully solved many challenging control tasks, its real-world applicability has been limited by the inability to ensure the safety of learned policies. We propose an approach to verifiable reinforcement learning
Bastani, Osbert +2 more
core
Advanced Functional Materials, EarlyView.Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley +1 more source
Anomaly Detection for Enhancing IoT Device Security Using Machine Learning: A Comparative Study of Four Lightweight Models Based on the IoT-23 Dataset [PDF]
ITM Web of ConferencesThis study focused on lightweight anomaly detection for Internet of Things (IoT) edge devices using the IoT-23 dataset. Four models were developed: Logistic Regression, Decision Tree (DT), Naive Bayes (NB), and Linear Support Vector Machine (SVM).
Gao Ziyuan
doaj +1 more source
Exclusive Biosynthesis of Pullulan Using Taguchi's Approach and Decision Tree Learning Algorithm by a Novel Endophytic Aureobasidium pullulans Strain. [PDF]
Polymers (Basel), 2023 Saber WIA, Al-Askar AA, Ghoneem KM.
europepmc +1 more source
Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-Agent Trajectories
, 2018 With the explosion in the availability of spatio-temporal tracking data in modern sports, there is an enormous opportunity to better analyse, learn and predict important events in adversarial group environments.
Denman, Simon +3 more
core +1 more source
Advanced Healthcare Materials, EarlyView.This work presents a novel, dynamically perfused, configurable microfluidic system for epidermis‐only (E and full‐thickness skin (FT SoC) growth, emulating human skin structure and barrier function. Upon TiO2 nanoparticle exposure, the system reveals compromised barrier integrity, reduced metabolic activity, increased permeability, and chemokine‐driven
Samantha Costa +7 more
wiley +1 more source