Yingqian Zhang
YOU?
Author Swipe
View article: Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration
Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration Open
Deep reinforcement learning (DRL) has emerged as an effective technique for dynamic algorithm configuration, particularly in evolutionary computation, enabling adaptive parameter updates during algorithmic execution. DRL-based methods have…
View article: The Dynamics of Trust in XAI: Assessing Perceived and Demonstrated Trust Across Interaction Modes and Risk Treatments
The Dynamics of Trust in XAI: Assessing Perceived and Demonstrated Trust Across Interaction Modes and Risk Treatments Open
The increasing use of artificial intelligence (AI) models across various fields has raised concerns about whether these models can meet user trust expectations. As a result, researchers are focusing on assessing AI models’ performance rela…
View article: Assessing and Quantifying Perceived Trust in Interpretable Clinical Decision Support
Assessing and Quantifying Perceived Trust in Interpretable Clinical Decision Support Open
Technical and ethical concerns impede the establishment of trust among healthcare professionals (HCPs) in developing artificial intelligence (AI)-based decision support. Yet, our understanding of trust models is constrained, and a standard…
View article: Generalizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Data
Generalizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Data Open
The Job-Shop Scheduling Problem (JSP) and Flexible Job-Shop Scheduling Problem (FJSP), are canonical combinatorial optimization problems with wide-ranging applications in industrial operations. In recent years, many online reinforcement le…
View article: Pair-Bid Auction Model for Optimized Network Slicing in 5G RAN
Pair-Bid Auction Model for Optimized Network Slicing in 5G RAN Open
Network slicing is a key 5G technology that enables multiple virtual networks to share physical infrastructure, optimizing flexibility and resource allocation. This involves Mobile Network Operators (MNO), Mobile Virtual Network Operators …
View article: A deception detection model by using integrated LLM with emotion features
A deception detection model by using integrated LLM with emotion features Open
View article: Offline reinforcement learning for learning to dispatch for job shop scheduling
Offline reinforcement learning for learning to dispatch for job shop scheduling Open
View article: Autoantibodies targeting the enteric nerve and non-myelin epitopes in relapsing-remitting multiple sclerosis: diagnostic relevance and viral mimicry
Autoantibodies targeting the enteric nerve and non-myelin epitopes in relapsing-remitting multiple sclerosis: diagnostic relevance and viral mimicry Open
Background Relapsing-remitting multiple sclerosis (RRMS) involves autoimmune responses against central nervous system (CNS) self-epitopes, potentially triggered by Epstein–Barr virus (EBV) and Human Herpesvirus 6 (HHV-6) reactivation. Obje…
View article: Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization Open
Deep reinforcement learning (DRL) has been widely used for dynamic algorithm configuration, particularly in evolutionary computation, which benefits from the adaptive update of parameters during the algorithmic execution. However, applying…
View article: Data science meets optimization II
Data science meets optimization II Open
View article: Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems
Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems Open
Neural combinatorial optimization (NCO) has gained significant attention due to the potential of deep learning to efficiently solve combinatorial optimization problems. NCO has been widely applied to job shop scheduling problems (JSPs) wit…
View article: Procedural Strategies in Transcatheter Aortic Valve Replacement for Patients With Small Aortic Annulus and Aortic Stenosis
Procedural Strategies in Transcatheter Aortic Valve Replacement for Patients With Small Aortic Annulus and Aortic Stenosis Open
Small aortic annulus is recognized as a critical risk factor in transcatheter aortic valve replacement, predisposing patients to prosthesis-patient mismatch. This case series examines 3 distinct anatomical subtypes of small aortic annulus …
View article: Key factors underpinning neuroimmune-metabolic-oxidative (NIMETOX) major depression in outpatients: paraoxonase 1 activity, reverse cholesterol transport, increased atherogenicity, protein oxidation, and differently expressed cytokine networks
Key factors underpinning neuroimmune-metabolic-oxidative (NIMETOX) major depression in outpatients: paraoxonase 1 activity, reverse cholesterol transport, increased atherogenicity, protein oxidation, and differently expressed cytokine networks Open
Background Major depressive disorder (MDD) is associated with neuro-immune – metabolic – oxidative (NIMETOX) pathways. Aims To examine the connections among NIMETOX pathways in outpatient MDD (OMDD) with and without metabolic syndrome (Met…
View article: Real-time policy for yard allocation of transshipment containers in a terminal
Real-time policy for yard allocation of transshipment containers in a terminal Open
In this article, we investigate the problem of allocating storage space in a container terminal's yard to transshipment containers. The main decision here concerns the block to which a container is assigned for storage until it is loaded l…
View article: Deep multi-objective reinforcement learning for utility-based infrastructural maintenance optimization
Deep multi-objective reinforcement learning for utility-based infrastructural maintenance optimization Open
View article: Optimization of 5G RAN Network Slicing based on Auction Models
Optimization of 5G RAN Network Slicing based on Auction Models Open
View article: Elevated Atherogenicity in Long COVID: A Systematic Review and Meta-Analysis
Elevated Atherogenicity in Long COVID: A Systematic Review and Meta-Analysis Open
View article: The physio-affective symptoms of Long COVID are strongly predicted by the severity of the acute infectious phase, and lowered antioxidants, nitric oxide, and alanine transaminase levels
The physio-affective symptoms of Long COVID are strongly predicted by the severity of the acute infectious phase, and lowered antioxidants, nitric oxide, and alanine transaminase levels Open
View article: Exploring the Value of Refined Management Based on Theory of Constraints in the Management of External Medical Devices in Hospital Sterilization and Supply Centers
Exploring the Value of Refined Management Based on Theory of Constraints in the Management of External Medical Devices in Hospital Sterilization and Supply Centers Open
To explore the value of refined management based on the Theory of Constraints (TOC) in the management of external medical devices in hospital sterilization and supply centers. Methods: This study selected external medical devices in a hosp…
View article: Railcar itinerary optimization in railway marshalling yards: A graph neural network based deep reinforcement learning method
Railcar itinerary optimization in railway marshalling yards: A graph neural network based deep reinforcement learning method Open
The goal of Railcar Itinerary Optimization in Marshalling Yards (RIO-MY) is to achieve an effective integrated operation plan for both train shunting operations and train makeup, with the aim of minimizing the railcar dwell time in the rai…
View article: Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems
Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems Open
Neural combinatorial optimization (NCO) has gained significant attention due to the potential of deep learning to efficiently solve combinatorial optimization problems. NCO has been widely applied to job shop scheduling problems (JSPs) wit…
View article: Do viral-associated pathways underlie the immune activation during the acute phase of severe major depression?
Do viral-associated pathways underlie the immune activation during the acute phase of severe major depression? Open
Background Major depressive disorder (MDD) and its most severe phenotype, major dysmood disorder (MDMD), are distinguished by the activation of the immune-inflammatory response system, T cell activation, and a relative T regulatory cell su…
View article: Graph neural networks for job shop scheduling problems: A survey
Graph neural networks for job shop scheduling problems: A survey Open
Job shop scheduling problems (JSSPs) represent a critical and challenging class of combinatorial optimization problems. Recent years have witnessed a rapid increase in the application of graph neural networks (GNNs) to solve JSSPs, albeit …
View article: Autoimmune responses to myelin-associated proteins as diagnostic and prognostic biomarkers of relapsing-remitting multiple sclerosis: associations with human herpesvirus-6 and Epstein-Barr Virus reactivation
Autoimmune responses to myelin-associated proteins as diagnostic and prognostic biomarkers of relapsing-remitting multiple sclerosis: associations with human herpesvirus-6 and Epstein-Barr Virus reactivation Open
Background The pathogenesis of relapsing-remitting multiple sclerosis (RRMS) is linked to autoimmune attacks against myelin proteins, and reactivation of Epstein-Barr virus (EBV) and human herpesvirus 6 (HHV-6). However, the connection bet…
View article: Do viral-associated pathways underlie the immune activation during the acute phase of severe major depression?
Do viral-associated pathways underlie the immune activation during the acute phase of severe major depression? Open
Background Major depressive disorder (MDD) and its most severe phenotype, major dysmood disorder (MDMD), are distinguished by the activation of the immune-inflammatory response system, T cell activation, and a relative T regulatory cell su…
View article: Chronic fatigue syndrome, depression, and anxiety symptoms due to relapsing-remitting multiple sclerosis are associated with reactivation of Epstein-Barr virus and Human Herpesvirus 6
Chronic fatigue syndrome, depression, and anxiety symptoms due to relapsing-remitting multiple sclerosis are associated with reactivation of Epstein-Barr virus and Human Herpesvirus 6 Open
Relapsing-remitting multiple sclerosis (RRMS) is defined by elevated IgG/IgA/IgM responses targeting Epstein-Barr Virus (EBV) nuclear antigen 1 (EBNA) and deoxyuridine-triphosphatases (dUTPases) of Human herpsesvirus-6 (HHV-6) and EBV. The…
View article: Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling
Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling Open
The Job Shop Scheduling Problem (JSSP) is a complex combinatorial optimization problem. While online Reinforcement Learning (RL) has shown promise by quickly finding acceptable solutions for JSSP, it faces key limitations: it requires exte…
View article: Wrapped Partial Label Dimensionality Reduction via Dependence Maximization
Wrapped Partial Label Dimensionality Reduction via Dependence Maximization Open
Partial label learning induces classifier from data with ambiguous supervision, where each instance is associated with a set of candidate labels but only one of which is valid. As a classic data preprocessing strategy, dimensionality reduc…
View article: Graph Neural Networks for Job Shop Scheduling Problems: A Survey
Graph Neural Networks for Job Shop Scheduling Problems: A Survey Open
Job shop scheduling problems (JSSPs) represent a critical and challenging class of combinatorial optimization problems. Recent years have witnessed a rapid increase in the application of graph neural networks (GNNs) to solve JSSPs, albeit …
View article: The combination of tumor mutational burden and T‐cell receptor repertoire predicts the response to immunotherapy in patients with advanced non–small cell lung cancer
The combination of tumor mutational burden and T‐cell receptor repertoire predicts the response to immunotherapy in patients with advanced non–small cell lung cancer Open
Tumor mutational burden (TMB) and T‐cell receptor (TCR) might predict the response to immunotherapy in patients with non–small cell lung cancer (NSCLC). However, the predictive value of the combination of TMB and TCR was not clear. Targete…