Private inference (PI) has emerged as a promising solution to execute computations on
encrypted data, safeguarding user privacy and model parameters in edge computing …

Electroencephalography (EEG) signals are crucial for investigating brain function and
cognitive processes. This study aims to address the challenges of efficiently recording and …

In the context of global trade, cross-border commodity pricing largely determines the
competitiveness and market share of businesses. However, existing methodologies often …

With the advancement of artificial intelligence, 3D human pose estimation-based systems for
sports training and posture correction have gained significant attention in adolescent sports …

This research focuses on real-time monitoring and analysis of track and field athletes,
addressing the limitations of traditional monitoring systems in terms of real-time performance …

Benefiting from cloud computing, today's early-stage quantum computers can be remotely
accessed via the cloud services, known as Quantum-as-a-Service (QaaS). However, it …

We introduce a principled approach to Outlier-Efficient Attention Layers via associative
memory models to reduce outlier emergence in large transformer-based model. Our main …

Risk analysis is an important business decision support task in customer relationship
management (CRM), involving the identification of potential risks or challenges that may …

This paper presents a novel methodology for predicting international bilateral trade flows,
emphasizing the growing importance of Preferential Trade Agreements (PTAs) in the global …

With the rapid proliferation of textual data, predicting long texts has emerged as a significant
challenge in the domain of natural language processing. Traditional text prediction methods …