Search Results for author: Wei Bao

Found 12 papers, 3 papers with code

Understanding Partial Multi-Label Learning via Mutual Information

no code implementations NeurIPS 2021 Xiuwen Gong, Dong Yuan, Wei Bao

To deal with ambiguities in partial multilabel learning (PML), state-of-the-art methods perform disambiguation by identifying ground-truth labels directly.

Multi-Label Learning

Fast Multi-label Learning

no code implementations31 Aug 2021 Xiuwen Gong, Dong Yuan, Wei Bao

The goal of this paper is to provide a simple method, yet with provable guarantees, which can achieve competitive performance without a complex training process.

Multi-Label Classification Multi-Label Learning

Boosting ship detection in SAR images with complementary pretraining techniques

no code implementations15 Mar 2021 Wei Bao, Meiyu Huang, Yaqin Zhang, Yao Xu, Xuejiao Liu, Xueshuang Xiang

In this paper, to resolve the problem of inconsistent imaging perspective between ImageNet and earth observations, we propose an optical ship detector (OSD) pretraining technique, which transfers the characteristics of ships in earth observations to SAR images from a large-scale aerial image dataset.

Representation Learning

The QXS-SAROPT Dataset for Deep Learning in SAR-Optical Data Fusion

1 code implementation15 Mar 2021 Meiyu Huang, Yao Xu, Lixin Qian, Weili Shi, Yaqin Zhang, Wei Bao, Nan Wang, Xuejiao Liu, Xueshuang Xiang

We obtain the SAR patches from SAR satellite GaoFen-3 images and the optical patches from Google Earth images.

DONE: Distributed Approximate Newton-type Method for Federated Edge Learning

2 code implementations10 Dec 2020 Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen, Wei Bao, Amir Rezaei Balef, Bing B. Zhou, Albert Y. Zomaya

In this work, we propose DONE, a distributed approximate Newton-type algorithm with fast convergence rate for communication-efficient federated edge learning.

Edge-computing

Federated Learning with Nesterov Accelerated Gradient Momentum Method

no code implementations18 Sep 2020 Zhengjie Yang, Wei Bao, Dong Yuan, Nguyen H. Tran, Albert Y. Zomaya

In this work, we focus on a version of FL based on NAG (FedNAG) and provide a detailed convergence analysis.

Federated Learning

Online Metric Learning for Multi-Label Classification

no code implementations12 Jun 2020 Xiuwen Gong, Jiahui Yang, Dong Yuan, Wei Bao

Specifically, in order to learn the new $k$NN-based metric, we first project instances in the training dataset into the label space, which make it possible for the comparisons of instances and labels in the same dimension.

Classification General Classification +2

Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation

4 code implementations29 Oct 2019 Canh T. Dinh, Nguyen H. Tran, Minh N. H. Nguyen, Choong Seon Hong, Wei Bao, Albert Y. Zomaya, Vincent Gramoli

There is an increasing interest in a fast-growing machine learning technique called Federated Learning, in which the model training is distributed over mobile user equipments (UEs), exploiting UEs' local computation and training data.

Federated Learning Privacy Preserving +1

Cannot find the paper you are looking for? You can Submit a new open access paper.