We study the optimization problem of choosing strings of finite length t...
Early detection and localization of pancreatic cancer can increase the 5...
Anomaly detection in multivariate time series data is of paramount impor...
For modern gradient-based optimization, a developmental landmark is
Nest...
Federated Learning (FL) has emerged as a promising approach for collabor...
The predominant centralized paradigm in educational data management curr...
We introduce a sum-of-squares SDP hierarchy approximating the ground-sta...
The goal of document-grounded dialogue (DocGD) is to generate a response...
Humans possess an extraordinary ability to create and utilize tools, all...
Most previous progress in object tracking is realized in daytime scenes ...
Efficient crowd counting models are urgently required for the applicatio...
In this paper, we revisit the class of iterative shrinkage-thresholding
...
Although the manipulating of the unmanned aerial manipulator (UAM) has b...
Although substantial efforts have been made using graph neural networks
...
Visual object tracking is an essential capability of intelligent robots....
Practical dialog systems need to deal with various knowledge sources, no...
Story visualization aims to generate a sequence of images to narrate eac...
For first-order smooth optimization, the research on the acceleration
ph...
Text-to-SQL parsing tackles the problem of mapping natural language ques...
In this paper, we propose a novel SQL guided pre-training framework STAR...
Most graph-to-text works are built on the encoder-decoder framework with...
This paper aims to improve the performance of text-to-SQL parsing by
exp...
In this paper, we introduce novel lightweight generative adversarial
net...
We introduce a memory-driven semi-parametric approach to text-to-image
g...
Story visualization aims to generate a sequence of images to narrate eac...
The importance of building text-to-SQL parsers which can be applied to n...
Recently, learned image compression methods have developed rapidly and
e...
This work aims to numerically construct exactly commuting matrices close...
Hierarchical Federated Learning (HFL) is introduced as a promising techn...
The task of converting a natural language question into an executable SQ...
Background Aims: Hepatic steatosis is a major cause of chronic liver...
Federated learning models must be protected against plagiarism since the...
Perceptual quality assessment of the videos acquired in the wilds is of ...
Most existing Siamese-based tracking methods execute the classification ...
Recent years have witnessed the fast evolution and promising performance...
We introduce the Unity Perception package which aims to simplify and
acc...
In this work, an adaptive edge element method is developed for an
H(curl...
Recently, the Siamese-based method has stood out from multitudinous trac...
Prior correlation filter (CF)-based tracking methods for unmanned aerial...
Autonomous systems (AS) carry out complex missions by continuously obser...
Depending on the application, radiological diagnoses can be associated w...
As a crucial robotic perception capability, visual tracking has been
int...
Visual object tracking, which is representing a major interest in image
...
In this work, we present a rather general class of transport distances o...
We propose a novel lightweight generative adversarial network for effici...
Transformer-based pre-trained language models (PLMs) have dramatically
i...
Aerial tracking, which has exhibited its omnipresent dedication and sple...
Ultrasound (US) is a critical modality for diagnosing liver fibrosis.
Un...
Nearly all existing techniques for automated video annotation (or captio...
The goal of this paper is to embed controllable factors, i.e., natural
l...