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08/20/2023
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning
Federated Learning (FL) is popular for its privacy-preserving and collab...
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08/08/2023
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers
Federated learning (FL) has been widely deployed to enable machine learn...
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07/21/2023
Chrion: Optimizing Recurrent Neural Network Inference by Collaboratively Utilizing CPUs and GPUs
Deploying deep learning models in cloud clusters provides efficient and ...
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07/01/2023
FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy
Recently, personalized federated learning (pFL) has attracted increasing...
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02/09/2023
Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples
Diffusion Models (DMs) achieve state-of-the-art performance in generativ...
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12/02/2022
FedALA: Adaptive Local Aggregation for Personalized Federated Learning
A key challenge in federated learning (FL) is the statistical heterogene...
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06/30/2022
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State
To train robust deep neural networks (DNNs), we systematically study sev...
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04/18/2022
Parallel Network with Channel Attention and Post-Processing for Carotid Arteries Vulnerable Plaque Segmentation in Ultrasound Images
Carotid arteries vulnerable plaques are a crucial factor in the screenin...
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12/30/2021
Resource-Efficient Deep Learning: A Survey on Model-, Arithmetic-, and Implementation-Level Techniques
Deep learning is pervasive in our daily life, including self-driving car...
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05/25/2021
Fast and Accurate Scene Parsing via Bi-direction Alignment Networks
In this paper, we propose an effective method for fast and accurate scen...
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06/21/2020
Off-Policy Self-Critical Training for Transformer in Visual Paragraph Generation
Recently, several approaches have been proposed to solve language genera...
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05/07/2020
ProSelfLC: Progressive Self Label Correction for Target Revising in Label Noise
In this work, we address robust deep learning under label noise (semi-su...
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04/21/2020
ParaCNN: Visual Paragraph Generation via Adversarial Twin Contextual CNNs
Image description generation plays an important role in many real-world ...
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02/07/2020
Object-Adaptive LSTM Network for Real-time Visual Tracking with Adversarial Data Augmentation
In recent years, deep learning based visual tracking methods have obtain...
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11/22/2019
Instance Cross Entropy for Deep Metric Learning
Loss functions play a crucial role in deep metric learning thus a variet...
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11/20/2019
ID-aware Quality for Set-based Person Re-identification
Set-based person re-identification (SReID) is a matching problem that ai...
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05/27/2019
Emphasis Regularisation by Gradient Rescaling for Training Deep Neural Networks with Noisy Labels
It is fundamental and challenging to train robust and accurate Deep Neur...
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03/28/2019
Improving MAE against CCE under Label Noise
Label noise is inherent in many deep learning tasks when the training se...
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03/27/2019
GAN-based Pose-aware Regulation for Video-based Person Re-identification
Video-based person re-identification deals with the inherent difficulty ...
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03/08/2019
Ranked List Loss for Deep Metric Learning
The objective of deep metric learning (DML) is to learn embeddings that ...
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11/22/2018
IEGAN: Multi-purpose Perceptual Quality Image Enhancement Using Generative Adversarial Network
Despite the breakthroughs in quality of image enhancement, an end-to-end...
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11/04/2018
