no code implementations • 6 Jan 2025 • Yuxin Ma, Zherui Zhang, Ran Cheng, Yaochu Jin, Kay Chen Tan
In the domain of multi-objective optimization, evolutionary algorithms are distinguished by their capability to generate a diverse population of solutions that navigate the trade-offs inherent among competing objectives.
no code implementations • 3 Dec 2024 • Luoxuan Weng, Yinghao Tang, Yingchaojie Feng, Zhuo Chang, Peng Chen, Ruiqin Chen, Haozhe Feng, Chen Hou, Danqing Huang, Yang Li, Huaming Rao, Haonan Wang, Canshi Wei, Xiaofeng Yang, Yuhui Zhang, Yifeng Zheng, Xiuqi Huang, Minfeng Zhu, Yuxin Ma, Bin Cui, Wei Chen
To achieve this unification, we design a domain knowledge incorporation module tailored for enterprise-specific BI tasks, an inter-agent communication mechanism to facilitate information sharing across the BI workflow, and a cell-based context management strategy to enhance context utilization efficiency in BI notebooks.
1 code implementation • 8 Aug 2024 • Zherui Zhang, Fan Yang, Ran Cheng, Yuxin Ma
Multi-objective evolutionary algorithms (MOEAs) have emerged as powerful tools for solving complex optimization problems characterized by multiple, often conflicting, objectives.
no code implementations • 7 Mar 2024 • Zezheng Feng, Yifan Jiang, Hongjun Wang, Zipei Fan, Yuxin Ma, Shuang-Hua Yang, Huamin Qu, Xuan Song
Recent achievements in deep learning (DL) have shown its potential for predicting traffic flows.
1 code implementation • 1 Dec 2023 • Haotian Gao, Renhe Jiang, Zheng Dong, Jinliang Deng, Yuxin Ma, Xuan Song
Spatiotemporal forecasting techniques are significant for various domains such as transportation, energy, and weather.
Ranked #1 on
Traffic Prediction
on EXPY-TKY
(using extra training data)
1 code implementation • 25 Aug 2023 • Fan Lei, Yuxin Ma, Stewart Fotheringham, Elizabeth Mack, ZiQi Li, Mehak Sachdeva, Sarah Bardin, Ross Maciejewski
As analysts create their spatial models, our framework flags potential issues with model parameter selections, utilizes template-based text generation to summarize model outputs, and links with external knowledge repositories to provide annotations that help to explain the model results.
1 code implementation • 10 Aug 2023 • Yansong Huang, Zherui Zhang, Ao Jiao, Yuxin Ma, Ran Cheng
Evolutionary multi-objective optimization (EMO) algorithms have been demonstrated to be effective in solving multi-criteria decision-making problems.
no code implementations • 18 Apr 2023 • Ping Gong, Yuxin Ma, Cheng Li, Xiaosong Ma, Sam H. Noh
In this paper, we primarily focus on understanding the data preprocessing pipeline for DNN Training in the public cloud.
no code implementations • 25 Jan 2023 • Yingchaojie Feng, Xingbo Wang, Bo Pan, Kam Kwai Wong, Yi Ren, Shi Liu, Zihan Yan, Yuxin Ma, Huamin Qu, Wei Chen
Our research explores how to provide explanations for NLIs to help users locate the problems and further revise the queries.
1 code implementation • 29 Jul 2022 • Yuxin Ma, Ping Gong, Jun Yi, Zhewei Yao, Cheng Li, Yuxiong He, Feng Yan
We identify the main accuracy impact factors in graph feature quantization and theoretically prove that BiFeat training converges to a network where the loss is within $\epsilon$ of the optimal loss of uncompressed network.
no code implementations • 5 May 2022 • Qingan Yan, Pan Ji, Nitin Bansal, Yuxin Ma, Yuan Tian, Yi Xu
In this paper, we deal with the problem of monocular depth estimation for fisheye cameras in a self-supervised manner.
no code implementations • 5 May 2022 • Pan Ji, Yuan Tian, Qingan Yan, Yuxin Ma, Yi Xu
The CNN depth effectively bootstraps the back-end optimization of SLAM and meanwhile the CNN uncertainty adaptively weighs the contribution of each feature point to the back-end optimization.
no code implementations • 3 May 2022 • Pan Ji, Qingan Yan, Yuxin Ma, Yi Xu
We present a robust and accurate depth refinement system, named GeoRefine, for geometrically-consistent dense mapping from monocular sequences.
1 code implementation • ICCV 2021 • Yuxin Ma, Yang Hua, Hanming Deng, Tao Song, Hao Wang, Zhengui Xue, Heng Cao, Ruhui Ma, Haibing Guan
Vessel segmentation is critically essential for diagnosinga series of diseases, e. g., coronary artery disease and retinal disease.
1 code implementation • 15 Sep 2020 • Yuxin Ma, Arlen Fan, Jingrui He, Arun Reddy Nelakurthi, Ross Maciejewski
Transfer Learning is intended to relax this assumption by modeling relationships between domains, and is often applied in deep learning applications to reduce the demand for labeled data and training time.
1 code implementation • 17 Jul 2019 • Yuxin Ma, Tiankai Xie, Jundong Li, Ross Maciejewski
Machine learning models are currently being deployed in a variety of real-world applications where model predictions are used to make decisions about healthcare, bank loans, and numerous other critical tasks.