Given the prevalence of rolling bearing fault diagnosis as a practical i...
In e-commerce platforms, the relevant recommendation is a unique scenari...
Large language models (LLMs) have demonstrated exceptional performance i...
Fault diagnosis of rolling bearings is of great significance for
post-ma...
Incremental random weight neural networks (IRWNNs) have gained attention...
Brain networks, graphical models such as those constructed from MRI, hav...
Prompt-tuning has received attention as an efficient tuning method in th...
Semantic medical image segmentation using deep learning has recently ach...
With tools like GitHub Copilot, automatic code suggestion is no longer a...
Language models are widely deployed to provide automatic text completion...
Image quality is important, and it can affect overall performance in ima...
Human brains are commonly modeled as networks of Regions of Interest (RO...
In neuroimaging analysis, functional magnetic resonance imaging (fMRI) c...
Dynamic facial expression recognition (FER) databases provide important ...
With the wide availability of large pre-trained language model checkpoin...
Human brains lie at the core of complex neurobiological systems, where t...
As a randomized learner model, SCNs are remarkable that the random weigh...
Electric Take-Off and Landing (eVTOL) aircraft is considered as the majo...
Accurate and unbiased examinations of skin lesions are critical for earl...
In this work, we propose an alternative parametrized form of the proxima...
Mapping the connectome of the human brain using structural or functional...
Learning using privileged information (LUPI) paradigm, which pioneered
t...
Dictionary learning aims at seeking a dictionary under which the trainin...
Dictionary learning aims to find a dictionary under which the training d...
Direct automatic segmentation of objects from 3D medical imaging, such a...
Interpretable brain network models for disease prediction are of great v...
Various applications of advanced air mobility (AAM) in urban environment...
Video quality assessment (VQA) is now a fastgrowing subject, beginning t...
This paper adds to the fundamental body of work on benchmarking the
robu...
Image classification models have achieved satisfactory performance on ma...
Deep neural networks are parameterised by weights that encode feature
re...
Retrieving relevant targets from an extremely large target set under
com...
This paper develops a new mathematical framework for denoising in blind
...
In this paper we consider the problem of constructing confidence interva...
Fully-Homomorphic Encryption (FHE) offers powerful capabilities by enabl...
With the rapid increase in cloud computing, concerns surrounding data
pr...
With the rapid increase in cloud computing, concerns surrounding data
pr...
Judgment prediction for legal cases has attracted much research efforts ...
This paper surveys benchmarking principles, machine learning devices
inc...
Previous survey papers offer knowledge of deep learning hardware devices...
Previous survey papers offer knowledge of deep learning hardware devices...
Algorithms for learning a dictionary under which a data in a given set h...
The optimization inspired network can bridge convex optimization and neu...
Super-resolution techniques are concerned with extracting fine-scale dat...
Traditional data quality control methods are based on users experience o...
This paper studies the problem of estimating origin-destination (OD) flo...
Many distributed machine learning (ML) systems adopt the non-synchronous...
Convolutional neural networks have led to significant breakthroughs in t...
The cardiothoracic ratio (CTR), a clinical metric of heart size in chest...
It is now well understood that convex programming can be used to estimat...