Autonomous 3D part assembly is a challenging task in the areas of roboti...
Social networks exhibit a complex graph-like structure due to the uncert...
Data valuation using Shapley value has emerged as a prevalent research d...
Universal domain adaptation (UniDA) aims to transfer knowledge from the
...
Federated learning (FL) is a distributed framework for collaboratively
t...
Data heterogeneity is an inherent challenge that hinders the performance...
During the deployment of deep neural networks (DNNs) on edge devices, ma...
Data compression has been widely adopted to release mobile devices from
...
Traditional federated optimization methods perform poorly with heterogen...
Collaborative multi-agent reinforcement learning (MARL) has been widely ...
The Coronavirus disease 2019 (COVID-19) outbreak quickly spread around t...
To learn camera-view invariant features for person Re-IDentification (Re...
In federated learning (FL), clients may have diverse objectives, merging...
Adversarial examples are inputs for machine learning models that have be...
Influenced by the great success of deep learning via cloud computing and...
Federated learning (FL) has emerged as an important machine learning par...
Despite federated learning endows distributed clients with a cooperative...
Graph neural networks (GNN) have been successful in many fields, and der...
By leveraging deep learning based technologies, the data-driven based
ap...
Conventional unsupervised multi-source domain adaptation(UMDA) methods a...
Due to people's emerging concern about data privacy, federated learning(...
To leverage enormous unlabeled data on distributed edge devices, we form...
Federated learning enables collaboratively training machine learning mod...
Federated learning is proposed as a machine learning setting to enable
d...
Peer-to-peer knowledge transfer in distributed environments has emerged ...
The recent rapid development of artificial intelligence (AI, mainly driv...
Predicting traffic conditions from online route queries is a challenging...
Bionic design refers to an approach of generative creativity in which a
...
Deep learning methods can play a crucial role in anomaly detection,
pred...
In this paper, we propose a way of synthesizing realistic images directl...
The present study proposes a deep learning model, named DeepSleepNet, fo...
It's useful to automatically transform an image from its original form t...
This paper proposes a practical approach to addressing limitations posed...
This paper presents the contribution to the third 'CHiME' speech separat...