Integrated sensing and communications (ISAC) has been recognized as a ke...
Multimodal recommendation exploits the rich multimodal information assoc...
Landslide is a natural disaster that can easily threaten local ecology,
...
Machine learning-based forecasting models are commonly used in Intellige...
General-purpose foundation models have become increasingly important in ...
Federated Graph Neural Network (FedGNN) has recently emerged as a rapidl...
Auction-based recommender systems are prevalent in online advertising
pl...
This paper proposes an integrated sensing, navigation, and communication...
Transfer learning has been widely adopted for few-shot classification. R...
It is anticipated that integrated sensing and communications (ISAC) woul...
Extremely large-scale array (XL-array) has emerged as a promising techno...
Multi-behavior recommendation, which exploits auxiliary behaviors (e.g.,...
Visual Commonsense Reasoning (VCR) remains a significant yet challenging...
The inclusion of the sensing functionality in the coming generations of
...
The booming development and huge market of micro-videos bring new e-comm...
Integrated sensing and communications (ISAC) is recognized as a key enab...
Machine learning based traffic forecasting models leverage sophisticated...
Recommendation systems make predictions chiefly based on users' historic...
This paper investigates intelligent reflecting surface (IRS) enabled
non...
Unmanned aerial vehicles (UAVs) as aerial base stations (BSs) are able t...
Contrastive Language Image Pretraining (CLIP) received widespread attent...
Flood disasters cause enormous social and economic losses. However, both...
Multi-behavior recommendation exploits multiple types of user-item
inter...
The degrees of freedom (DoFs) attained in monostatic integrated sensing ...
This paper investigates intelligent reflecting surface (IRS) enabled
non...
Integrated Sensing and Communication (ISAC) is recognized as a promising...
In this letter, we study the parameter estimation performance for monost...
Many multimodal recommender systems have been proposed to exploit the ri...
The space-air-ground-sea integrated network (SAGSIN) plays an important ...
To support the unprecedented growth of the Internet of Things (IoT)
appl...
Session-based recommendation (SBR) has drawn increasingly research atten...
This paper proposes an integrated sensing, jamming, and communications (...
In this paper, we propose an efficient algorithm for the network slicing...
Computational intelligence-based ocean characteristics forecasting
appli...
Meta-learning model can quickly adapt to new tasks using few-shot labele...
Graph Convolution Networks (GCNs) manifest great potential in recommenda...
In the era of big data, anonymity is recognized as an important attribut...
Dual-functional radar-communication (DFRC) is a promising new solution t...
In this letter, we propose an interference exploitation symbol-level
pre...
The pandemic of COVID-19 has caused millions of infectious. Due to the
f...
Convolutional Neural Network (CNN) is one of the most significant networ...
As important side information, attributes have been widely exploited in ...
In this paper, we focus on 1-bit precoding for large-scale antenna syste...
Most existing recommender systems represent a user's preference with a
f...
In this paper, we focus on 1-bit precoding approaches for downlink massi...
Matrix completion focuses on recovering a matrix from a small subset of ...
Recently, low-rank tensor completion has become increasingly attractive ...
We study the multi-user massive multiple-input-single-output (MISO) and ...
In this paper, we focus on the coexistence between a MIMO radar and cell...
Currently, low-rank tensor completion has gained cumulative attention in...