AugDiff: Diffusion-Based Feature Augmentation for Multiple Instance Learning in Whole Slide Image

Information Science, Computer Science, Artificial Intelligence, Medicine, Oncology,
feature augmentation   diffusion model   multiple instance learning   whole slide image   computational pathology   deep learning   image generation  

Diffusion-Based Feature Augmentation: A Novel Approach for Multiple Instance Learning in Whole Slide Images Academic Background and Research Motivation In computational pathology, effectively analyzing Whole Slide Images (WSIs) is a burgeoning area of research. WSIs are ultra-high-resolution images with a broad field of view and are widely employed...

Higher-Order Directed Community Detection by a Multiobjective Evolutionary Framework

Information Science, Computer Science, Artificial Intelligence,
higher-order community detection   directed networks   information flow   multiobjective optimization   network topology   evolutionary algorithm   motif density  

The paper, titled “Higher-Order Directed Community Detection by a Multiobjective Evolutionary Framework”, authored by Jing Xiao, Jing Cao, and Xiao-Ke Xu, was published in the IEEE Transactions on Artificial Intelligence in December 2024. The authors introduce a novel approach for detecting higher-order communities in directed networks, addressing ...

Cost-Efficient Feature Selection for Horizontal Federated Learning

Information Science, Computer Science, Artificial Intelligence,
Federated Learning   Feature Selection   Multiobjective Optimization   Mutual Information   Clustering  

Research on Cost-Efficient Feature Selection in Horizontal Federated Learning Background and Motivation As Federated Learning (FL) is increasingly recognized as a distributed machine learning paradigm that safeguards data privacy, its application to multi-client scenarios has garnered significant attention. In Horizontal Federated Learning (HFL), a...

Self-Model-Free Learning versus Learning with External Rewards in Information-Constrained Environments

Information Science, Computer Science, Artificial Intelligence,
Reinforcement Learning   Information Loss   Adversarial Learning   Jamming Attacks   Autonomous Decision Making  

Self-Model-Free Learning vs. Learning with External Rewards in Information-Constrained Environments: A New Reinforcement Learning Framework In recent years, with the development of networks and artificial intelligence systems, networked learning mechanisms face significant security challenges. In the domain of reinforcement learning (RL), the loss ...

Spatio-Temporal Graph-Based Generation and Detection of Adversarial False Data Injection Evasion Attacks in Smart Grids

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence,
smart grids   false data injection attacks   adversarial attacks   spatio-temporal graphs   graph neural networks   machine learning   cybersecurity  

Title: Generating and Detecting Spatio-Temporal Graph-Based Adversarial False Data Injection Evasion Attacks in Smart Grids Background With the continuous development of modern smart grids, the grid, as a typical Cyber-Physical System (CPS), faces numerous security threats due to the extensive exchange of data between its components. Among these, F...

Simplified Kernel-Based Cost-Sensitive Broad Learning System for Imbalanced Fault Diagnosis

Engineering, Mechanical Engineering, Information Science, Computer Science, Artificial Intelligence,
fault diagnosis   imbalanced data   broad learning system   cost-sensitive learning   kernel mapping  

Research Report on the Simplified Kernel-Based Cost-Sensitive Broad Learning System (SKCSBLS) for Imbalanced Fault Diagnosis Research Background and Significance With the advent of Industry 4.0, smart manufacturing increasingly relies on industrial big data analytics. By extracting critical insights from machine operation data, the effectiveness of...