With the fast growth of parameter size, it becomes increasingly challeng...
Blended learning is generally defined as the combination of traditional
...
This paper primarily focuses on analyzing the problems and proposing
sol...
Educational Data Mining (EDM) has emerged as a vital field of research, ...
Micro-videos platforms such as TikTok are extremely popular nowadays. On...
Hash representation learning of multi-view heterogeneous data is the key...
Membership Inference Attack (MIA) identifies whether a record exists in ...
Large-scale text-to-image (T2I) diffusion models have been extended for
...
Graph Neural Network (GNN)-based models have become the mainstream appro...
EduChat (https://www.educhat.top/) is a large-scale language model
(LLM)...
Living needs refer to the various needs in human's daily lives for survi...
Understanding and characterizing the vulnerability of urban infrastructu...
The SnakeCLEF2023 competition aims to the development of advanced algori...
Automated Machine Learning (AutoML) techniques have recently been introd...
Since 2021, China has deployed more than 2.1 million 5G base stations to...
Origin-destination (OD) flow modeling is an extensively researched subje...
The Origin-Destination (OD) networks provide an estimation of the flow o...
Origin-destination (OD) flow, which contains valuable population mobilit...
Graph convolutional networks (GCNs) have become prevalent in recommender...
Millions of slum dwellers suffer from poor accessibility to urban servic...
The innovations in reactive synthesis from Linear Temporal Logics over
f...
Low-light images often suffer from severe noise, low brightness, low
con...
Human multimodal emotion recognition (MER) aims to perceive human emotio...
Graph Neural Networks (GNNs) have been recently introduced to learn from...
Graph Neural Network(GNN) based social recommendation models improve the...
Monitoring sustainable development goals requires accurate and timely
so...
Federated learning (FL) is a promising technique for addressing the risi...
Model parallelism has become necessary to train large neural networks.
H...
Complementation of nondeterministic Büchi automata (BAs) is an important...
For Prognostics and Health Management (PHM) of Lithium-ion (Li-ion)
batt...
Existing deep learning based HDRTV reconstruction methods assume one kin...
Objective geometry quality assessment of point clouds is essential to
ev...
Recently, knowledge-enhanced pre-trained language models (KEPLMs) improv...
With the outbreak of today's streaming data, sequential recommendation i...
Deep reinforcement learning (DRL) has been proven its efficiency in capt...
Distributed synchronized GPU training is commonly used for deep learning...
Existing recommender systems extract the user preference based on learni...
Spatiotemporal activity prediction, aiming to predict user activities at...
Recommender systems are prone to be misled by biases in the data. Models...
In recent years, China has witnessed the proliferation and success of th...
Recommender systems are playing an increasingly important role in allevi...
After a developer submits code, corresponding test cases arise to ensure...
While hyper-parameters (HPs) are important for knowledge graph (KG) lear...
The exposure sequence is being actively studied for user interest modeli...
Most modern recommender systems predict users preferences with two
compo...
The development of personalized recommendation has significantly improve...
The support set is a key to providing conditional prior for fast adaptio...
The disadvantaged population is often underserved and marginalized in
te...
Graph Neural Networks (GNNs) have shown promising results in various tas...
Federated optimization (FedOpt), which targets at collaboratively traini...