Histological examination is a crucial step in an autopsy; however, the
t...
Object detection via inaccurate bounding boxes supervision has boosted a...
The first-principles-based effective Hamiltonian is widely used to predi...
Deep learning has been extensively used in wireless communication proble...
Mid-term electricity load forecasting (LF) plays a critical role in powe...
In Lifelong Learning (LL), agents continually learn as they encounter ne...
Using a shared vocabulary is common practice in Multilingual Neural Mach...
In this paper, we present ZeroPrompt (Figure 1-(a)) and the correspondin...
Different from conventional federated learning, personalized federated
l...
Federated learning (FL) is a prospective distributed machine learning
fr...
Efficiently running federated learning (FL) on resource-constrained devi...
Despite the significant advancements in keyphrase extraction and keyphra...
Edge computing has been getting a momentum with ever-increasing data at ...
Digital twins have shown a great potential in supporting the development...
With the continuous growth in communication network complexity and traff...
Communication load balancing aims to balance the load between different
...
Knowledge graph embedding (KGE) that maps entities and relations into ve...
In cellular networks, User Equipment (UE) handoff from one Base Station ...
Hacking and false data injection from adversaries can threaten power gri...
Traditional feature selections need to know the feature space before
lea...
A hole is an induced cycle of length at least four, and an odd hole is a...
Safety has been recognized as the central obstacle to preventing the use...
Radio Access Networks (RANs) for telecommunications represent large
aggl...
Machine learning (ML) tasks are one of the major workloads in today's ed...
Machine Translation Quality Estimation (QE) is the task of evaluating
tr...
Neural models that do not rely on pre-training have excelled in the keyp...
User behavior data produced during interaction with massive items in the...
Human modeling and relighting are two fundamental problems in computer v...
Federated semi-supervised learning (FSSL), facilitates labeled clients a...
Recently, the unified streaming and non-streaming two-pass (U2/U2++)
end...
In this paper, we present TrimTail, a simple but effective emission
regu...
The recently proposed Conformer architecture which combines convolution ...
The building sector has been recognized as one of the primary sectors fo...
Federated learning (FL) has gained significant attention recently as a
p...
Federated learning (FL) facilitates multiple clients to jointly train a
...
Federated learning (FL) trains machine learning (ML) models on devices u...
Missing data is an inevitable and common problem in data-driven intellig...
Extracting the latent information in high-dimensional and incomplete mat...
A novel network for enhancement to underwater images is proposed in this...
Masked image modeling (MIM), an emerging self-supervised pre-training me...
Deep learning techniques have shown promising results in image compressi...
Federated learning has gained great attention recently as a privacy-enha...
Time series anomaly detection is of critical importance for the reliable...
Early fault detection (EFD) of rotating machines is important to decreas...
Early fault detection (EFD) of rolling bearings can recognize slight
dev...
High-dimensional and sparse (HiDS) matrices are omnipresent in a variety...
A High-dimensional and sparse (HiDS) matrix is frequently encountered in...
High-dimensional and sparse (HiDS) matrices are frequently adopted to
de...
Recently, we made available WeNet, a production-oriented end-to-end spee...
Battery energy storage systems can be used for peak demand reduction in ...