no code implementations • 29 Apr 2024 • Weike Peng, Jiaxin Gao, Yuntian Chen, Shengwei Wang
To ascertain the merits of the proposed FL-XGBoost method, a comparative analysis is conducted between separate and centralized models to address a classical binary classification problem in geoenergy sector.
no code implementations • 29 Feb 2024 • Ziyu Yue, Jiaxin Gao, Sihan Xie, Yang Liu, Zhixun Su
The visibility of real-world images is often limited by both low-light and low-resolution, however, these issues are only addressed in the literature through Low-Light Enhancement (LLE) and Super- Resolution (SR) methods.
no code implementations • 10 Dec 2023 • Jiaxin Gao, Yuxiao Hu, Qinglong Cao, Siqi Dai, Yuntian Chen
Time series forecasting (TSF) holds significant importance in modern society, spanning numerous domains.
no code implementations • 4 Dec 2023 • Jiaxin Gao, Qinglong Cao, Yuntian Chen
Utilizing the MoE framework, MoE-AMC seamlessly combines the strengths of LSRM (a Transformer-based model) for handling low SNR signals and HSRM (a ResNet-based model) for high SNR signals.
1 code implementation • 19 Oct 2023 • Yaohua Liu, Jiaxin Gao, Xianghao Jiao, Zhu Liu, Xin Fan, Risheng Liu
Adversarial Training (AT), pivotal in fortifying the robustness of deep learning models, is extensively adopted in practical applications.
1 code implementation • 9 Oct 2023 • Jingliang Duan, Wenxuan Wang, Liming Xiao, Jiaxin Gao, Shengbo Eben Li
Reinforcement learning (RL) has proven to be highly effective in tackling complex decision-making and control tasks.
no code implementations • 11 Sep 2023 • Jiaxin Gao, Ziyu Yue, Yaohua Liu, Sihan Xie, Xin Fan, Risheng Liu
Super-resolution tasks oriented to images captured in ultra-dark environments is a practical yet challenging problem that has received little attention.
no code implementations • 28 Jul 2023 • Risheng Liu, Jiaxin Gao, Xuan Liu, Xin Fan
The complexity of learning problems, such as Generative Adversarial Network (GAN) and its variants, multi-task and meta-learning, hyper-parameter learning, and a variety of real-world vision applications, demands a deeper understanding of their underlying coupling mechanisms.
1 code implementation • 30 May 2023 • Jiaxin Gao, WenBo Hu, Yuntian Chen
Long-term time series forecasting (LTSF) is a crucial aspect of modern society, playing a pivotal role in facilitating long-term planning and developing early warning systems.
no code implementations • 25 May 2023 • Xianghao Jiao, Yaohua Liu, Jiaxin Gao, Xinyuan Chu, Risheng Liu, Xin Fan
In light of the significant progress made in the development and application of semantic segmentation tasks, there has been increasing attention towards improving the robustness of segmentation models against natural degradation factors (e. g., rain streaks) or artificially attack factors (e. g., adversarial attack).
no code implementations • 17 May 2023 • Xiaofeng Liu, Jiaxin Gao, Yaohua Liu, Risheng Liu, Nenggan Zheng
Recently significant progress has been made in human action recognition and behavior prediction using deep learning techniques, leading to improved vision-based semantic understanding.
no code implementations • 17 May 2023 • Xiaofeng Liu, Jiaxin Gao, Xin Fan, Risheng Liu
Contemporary Low-Light Image Enhancement (LLIE) techniques have made notable advancements in preserving image details and enhancing contrast, achieving commendable results on specific datasets.
no code implementations • 5 Oct 2022 • Jiaxin Gao, WenBo Hu, Dongxiao Zhang, Yuntian Chen
Accurate electrical load forecasting is beneficial for better scheduling of electricity generation and saving electrical energy.
no code implementations • 20 May 2022 • Risheng Liu, Jiaxin Gao, Xuan Liu, Xin Fan
In past years, the minimax type single-level optimization formulation and its variations have been widely utilized to address Generative Adversarial Networks (GANs).
1 code implementation • 27 Jan 2021 • Risheng Liu, Jiaxin Gao, Jin Zhang, Deyu Meng, Zhouchen Lin
Bi-Level Optimization (BLO) is originated from the area of economic game theory and then introduced into the optimization community.