A5101984194- Opportunistic and Delay-Tolerant Networks
- Domain Adaptation and Few-Shot Learning
- Virtual Reality Applications and Impacts
- Remote-Sensing Image Classification
- Caching and Content Delivery
- Face and Expression Recognition
- Advanced Image Processing Techniques
- Sparse and Compressive Sensing Techniques
- Augmented Reality Applications
- Stochastic Gradient Optimization Techniques
- Image and Signal Denoising Methods
- Cooperative Communication and Network Coding
- Interactive and Immersive Displays
- Neural dynamics and brain function
- Digital Media and Visual Art
- Education and Learning Interventions
- Neural Networks and Applications
- Vehicular Ad Hoc Networks (VANETs)
- Hearing Loss and Rehabilitation
- Action Observation and Synchronization
Huazhong Agricultural University
2023-2024
Harbin Institute of Technology
2022
Hong Kong Metropolitan University
2022
Southwest Jiaotong University
2016-2017
Zhejiang University
2017
In the vehicular ad hoc networks (VANETs), caching is a very promising technique to mitigate transmission burden and improve consumers' Quality of Experience (QoE) in terms latency. Determining placement policy one most important issues maximize gain. this paper, based on cloud-based VANET architecture corresponding content retrieve process, which jointly considers at layer roadside unit (RSU) proposed. More specifically, problem modeled as an optimization minimize average latency while...
Caching is a promising technology to alleviate the transmission pressure of 5G heterogeneous networks. To overcome drawbacks existing caching schemes that ignore heterogeneity or cooperation characteristics networks, this paper proposes cooperation-based scheme (CBCS). Based on scheme, average energy consumption incurred by user equipment (UE) obtain its desired content formulated as an NP-hard optimization problem, and two greedy heuristic algorithms are developed solve problem. In...
Decentralized Stochastic Gradient Descent (D-SGD) represents an efficient communication approach tailored for mastering insights from vast, distributed datasets. Inspired by parallel optimization paradigms, the incorporation of minibatch serves to diminish variance, consequently expediting process. Nevertheless, as per our current understanding, existing literature has not thoroughly explored learning theory foundation Minibatch (DM-SGD). In this paper, we try address theoretical gap...
Wearable technology is very popular in recent years.Since the advent of Glass Google, lots kinds wearable devices have been developed.There more and education.Through literature field survey, researchers conducted studies on its application education.We find that scope involves many fields, such as medical, entertainment, health, military, education, so on.The effective use education needs to improve meet education.
Recently, some mixture algorithms of pointwise and pairwise learning (PPL) have been formulated by employing the hybrid error metric "pointwise loss + loss" shown empirical effectiveness on feature selection, ranking recommendation tasks. However, to best our knowledge, theory foundation PPL has not touched in existing works. In this paper, we try fill theoretical gap investigating generalization properties PPL. After extending definitions algorithmic stability setting, establish...
Recently, some mixture algorithms of pointwise and pairwise learning (PPL) have been formulated by employing the hybrid error metric “pointwise loss + loss” shown empirical effectiveness on feature selection, ranking recommendation tasks. However, to best our knowledge, theory foundation PPL has not touched in existing works. In this paper, we try fill theoretical gap investigating generalization properties PPL. After extending definitions algorithmic stability setting, establish...