2 code implementations • 10 Mar 2021 • Cheng Cui, Ruoyu Guo, Yuning Du, Dongliang He, Fu Li, Zewu Wu, Qiwen Liu, Shilei Wen, Jizhou Huang, Xiaoguang Hu, dianhai yu, Errui Ding, Yanjun Ma
Recently, research efforts have been concentrated on revealing how pre-trained model makes a difference in neural network performance.
1 code implementation • 21 Jun 2023 • Congxi Xiao, Jingbo Zhou, Jizhou Huang, Tong Xu, Hui Xiong
However, urban graphs usually can be observed to possess a unique spatial heterophily property; that is, the dissimilarity of neighbors at different spatial distances can exhibit great diversity.
5 code implementations • ICCV 2021 • Min Yang, Dongliang He, Miao Fan, Baorong Shi, Xuetong Xue, Fu Li, Errui Ding, Jizhou Huang
Components orthogonal to the global image representation are then extracted from the local information.
1 code implementation • 21 Jan 2019 • Dongliang He, Xiang Zhao, Jizhou Huang, Fu Li, Xiao Liu, Shilei Wen
The task of video grounding, which temporally localizes a natural language description in a video, plays an important role in understanding videos.
no code implementations • 22 Dec 2020 • Congxi Xiao, Jingbo Zhou, Jizhou Huang, An Zhuo, Ji Liu, Haoyi Xiong, Dejing Dou
Furthermore, to transfer the firsthand knowledge (witted in epicenters) to the target city before local outbreaks, we adopt a novel adversarial encoder framework to learn "city-invariant" representations from the mobility-related features for precise early detection of high-risk neighborhoods, even before any confirmed cases known, in the target city.
no code implementations • 29 Apr 2021 • Ji Liu, Jizhou Huang, Yang Zhou, Xuhong LI, Shilei Ji, Haoyi Xiong, Dejing Dou
Because of laws or regulations, the distributed data and computing resources cannot be directly shared among different regions or organizations for machine learning tasks.
no code implementations • 6 May 2020 • Jizhou Huang, Haifeng Wang, Haoyi Xiong, Miao Fan, An Zhuo, Ying Li, Dejing Dou
While these strategies have effectively dealt with the critical situations of outbreaks, the combination of the pandemic and mobility controls has slowed China's economic growth, resulting in the first quarterly decline of Gross Domestic Product (GDP) since GDP began to be calculated, in 1992.
no code implementations • 20 Aug 2021 • Yibo Sun, Jizhou Huang, Chunyuan Yuan, Miao Fan, Haifeng Wang, Ming Liu, Bing Qin
We approach this task as a sequence tagging problem, where the goal is to produce <POI name, accessibility label> pairs from unstructured text.
no code implementations • 24 Sep 2021 • Linlang Jiang, Jingbo Zhou, Tong Xu, Yanyan Li, Hao Chen, Jizhou Huang, Hui Xiong
To that end, we propose an Adversarial Neural Trip Recommendation (ANT) framework to tackle the above challenges.
no code implementations • KDD 2021 • Yudong Chen, Xin Wang, Miao Fan, Jizhou Huang, Shengwen Yang, and Wenwu Zhu.
Next point-of-interest (POI) recommendation is a hot research field where a recent emerging scenario, next POI to search recommendation, has been deployed in many online map services such as Baidu Maps.
no code implementations • 17 Mar 2022 • Jizhou Huang, Haifeng Wang, Yibo Sun, Yunsheng Shi, Zhengjie Huang, An Zhuo, Shikun Feng
One of the main reasons for this plateau is the lack of readily available geographic knowledge in generic PTMs.
no code implementations • 15 Aug 2022 • Jizhou Huang, Zhengjie Huang, Xiaomin Fang, Shikun Feng, Xuyi Chen, Jiaxiang Liu, Haitao Yuan, Haifeng Wang
In this work, we focus on modeling traffic congestion propagation patterns to improve ETA performance.
no code implementations • 26 Nov 2022 • Congxi Xiao, Jingbo Zhou, Jizhou Huang, HengShu Zhu, Tong Xu, Dejing Dou, Hui Xiong
The core idea of such a framework is to firstly pre-train a basis (or master) model over the URG, and then to adaptively derive specific (or slave) models from the basis model for different regions.
no code implementations • 27 Jan 2024 • Daniel Hsu, Jizhou Huang, Brendan Juba
In this work, we give positive and negative results on auditing for Gaussian distributions: On the positive side, we present an alternative approach to leverage these advances in agnostic learning and thereby obtain the first polynomial-time approximation scheme (PTAS) for auditing nontrivial combinatorial subgroup fairness: we show how to audit statistical notions of fairness over homogeneous halfspace subgroups when the features are Gaussian.