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04/16/2023
Handling Heavy Occlusion in Dense Crowd Tracking by Focusing on the Heads
With the rapid development of deep learning, object detection and tracki...
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03/20/2023
FedMAE: Federated Self-Supervised Learning with One-Block Masked Auto-Encoder
Latest federated learning (FL) methods started to focus on how to use un...
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02/23/2023
FedIL: Federated Incremental Learning from Decentralized Unlabeled Data with Convergence Analysis
Most existing federated learning methods assume that clients have fully ...
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02/17/2023
Random Padding Data Augmentation
The convolutional neural network (CNN) learns the same object in differe...
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12/05/2022
Enhancing Quantum Adversarial Robustness by Randomized Encodings
The interplay between quantum physics and machine learning gives rise to...
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10/26/2022
Hierarchical Federated Learning with Momentum Acceleration in Multi-Tier Networks
In this paper, we propose Hierarchical Federated Learning with Momentum ...
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08/31/2021
Fast Multi-label Learning
Embedding approaches have become one of the most pervasive techniques fo...
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02/24/2021
A Novel Graph-based Computation Offloading Strategy for Workflow Applications in Mobile Edge Computing
With the fast development of mobile edge computing (MEC), there is an in...
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11/12/2020
A Fast and Scalable Authentication Scheme in IoT for Smart Living
Numerous resource-limited smart objects (SOs) such as sensors and actuat...
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09/18/2020
Federated Learning with Nesterov Accelerated Gradient Momentum Method
Federated learning (FL) is a fast-developing technique that allows multi...
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09/04/2020
ServiceNet: A P2P Service Network
Given a large number of online services on the Internet, from time to ti...
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06/12/2020
