In spite of the excellent strides made by end-to-end (E2E) models in spe...
Self-supervised learning (SSL) proficiency in speech-related tasks has d...
While language-guided image manipulation has made remarkable progress, t...
As mobile devices become increasingly popular for video streaming, it's
...
Neural Radiance Fields (NeRF) is a revolutionary approach for rendering
...
Cloud gaming is a multi-billion dollar industry. A client in cloud gamin...
ChatGPT has drawn considerable attention from both the general public an...
Learning with noisy labels is an important topic for scalable training i...
Federated bilevel optimization (FBO) has shown great potential recently ...
Adversarial detection aims to determine whether a given sample is an
adv...
While large language models (LLMs) have been successfully applied to var...
A covariance matrix with a special pattern (e.g., sparsity or block
stru...
Online optimization has gained increasing interest due to its capability...
Estimating a covariance matrix is central to high-dimensional data analy...
Ensemble methods can deliver surprising performance gains but also bring...
Image token removal is an efficient augmentation strategy for reducing t...
While person Re-identification (Re-ID) has progressed rapidly due to its...
Retrieval based open-domain QA systems use retrieved documents and
answe...
Many multi-object tracking (MOT) methods follow the framework of "tracki...
Face clustering is an essential task in computer vision due to the explo...
During the COVID-19 epidemic in China, millions of workers in tech compa...
Only a few cherry-picked robust augmentation policies are beneficial to
...
Vital importance has necessity to be attached to cooperation in multi-ag...
Large-scale fine-grained image retrieval has two main problems. First, l...
A popular application of federated learning is using many clients to tra...
Few-shot semantic segmentation is a challenging task of predicting objec...
Joint extraction of entities and relations from unstructured texts is a
...
Single image super-resolution (SISR) aims to reconstruct high-resolution...
Current deep learning based disease diagnosis systems usually fall short...
We introduce a stochastic version of Taylor's expansion and Mean Value
T...
With the spread and development of new epidemics, it is of great referen...
A new variational mode decomposition (VMD) based deep learning approach ...
We present a novel blockchain based service for proving the provenance o...
In recent years, deep-networks-based hashing has become a leading approa...
Deep-networks-based hashing has become a leading approach for large-scal...
Using FPGAs to accelerate ConvNets has attracted significant attention i...
With the advantage of high mobility, Unmanned Aerial Vehicles (UAVs) are...
In this paper, we try to predict the winning team of a match in the
mult...
This paper studied generating natural languages at particular contexts o...