Nanqing Dong | DeepAI

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Xiaodan Liang
197 publications
Eric P Xing
147 publications
Yi Zhou
114 publications
Min Xu
72 publications
Eric Xing
70 publications
Aleš Leonardis
63 publications
Wei Dai
62 publications
Pengtao Xie
59 publications
Hao Zhang
58 publications
Yongxin Yang
55 publications
Michael Kampffmeyer
47 publications

∙ 07/02/2023

Defending Against Malicious Behaviors in Federated Learning with Blockchain

In the era of deep learning, federated learning (FL) presents a promisin...

0 Nanqing Dong, et al. ∙

∙ 11/16/2022

Region Proposal Network Pre-Training Helps Label-Efficient Object Detection

Self-supervised pre-training, based on the pretext task of instance disc...

0 Linus Ericsson, et al. ∙

∙ 11/05/2022

FLock: Defending Malicious Behaviors in Federated Learning with Blockchain

Federated learning (FL) is a promising way to allow multiple data owners...

0 Nanqing Dong, et al. ∙

∙ 06/30/2022

Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images

Using decentralized data for federated training is one promising emergin...

0 Nanqing Dong, et al. ∙

∙ 04/19/2022

Revisiting Vicinal Risk Minimization for Partially Supervised Multi-Label Classification Under Data Scarcity

Due to the high human cost of annotation, it is non-trivial to curate a ...

14 Nanqing Dong, et al. ∙

∙ 10/06/2021

Cooperative Multi-Agent Actor-Critic for Privacy-Preserving Load Scheduling in a Residential Microgrid

As a scalable data-driven approach, multi-agent reinforcement learning (...

12 Zhaoming Qin, et al. ∙

∙ 09/15/2021

Federated Contrastive Learning for Decentralized Unlabeled Medical Images

A label-efficient paradigm in computer vision is based on self-supervise...

0 Nanqing Dong, et al. ∙

∙ 06/18/2021

Residual Contrastive Learning for Joint Demosaicking and Denoising

The breakthrough of contrastive learning (CL) has fueled the recent succ...

0 Nanqing Dong, et al. ∙

∙ 05/20/2021

Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification

Entanglement is a physical phenomenon, which has fueled recent successes...

23 Nanqing Dong, et al. ∙

∙ 11/28/2020

Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels

The data-driven nature of deep learning models for semantic segmentation...

15 Nanqing Dong, et al. ∙

∙ 05/28/2019

Adversarial Domain Adaptation Being Aware of Class Relationships

Adversarial training is a useful approach to promote the learning of tra...

1 Zeya Wang, et al. ∙

∙ 10/08/2018

Toward Understanding the Impact of Staleness in Distributed Machine Learning

Many distributed machine learning (ML) systems adopt the non-synchronous...

2 Wei Dai, et al. ∙

∙ 07/29/2018

Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images

Convolutional neural networks have led to significant breakthroughs in t...

0 Nanqing Dong, et al. ∙

∙ 07/10/2018

Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio

The cardiothoracic ratio (CTR), a clinical metric of heart size in chest...

2 Nanqing Dong, et al. ∙

∙ 04/20/2018

ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation

Salient segmentation aims to segment out attention-grabbing regions, a c...

0 Michael Kampffmeyer, et al. ∙

∙ 03/26/2017

SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays

Chest X-ray (CXR) is one of the most commonly prescribed medical imaging...

0 Wei Dai, et al. ∙

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