1 code implementation • 6 Mar 2024 • Xinyuan Wang, Dongjie Wang, Wangyang Ying, Rui Xie, Haifeng Chen, Yanjie Fu
A deep Q-network, pre-trained with the original features and their corresponding pseudo labels, is employed to improve the efficacy of the exploration process in feature selection.
no code implementations • 6 Mar 2024 • Wangyang Ying, Dongjie Wang, Haifeng Chen, Yanjie Fu
(2) We leverage the trained feature subset utility evaluator as a gradient provider to guide the identification of the optimal feature subset embedding;(3) We decode the optimal feature subset embedding to autoregressively generate the best feature selection decision sequence with autostop.
no code implementations • 3 Oct 2023 • Xuanming Hu, Wei Fan, Dongjie Wang, Pengyang Wang, Yong Li, Yanjie Fu
We design several experiments to indicate that our framework can outperform compared to other generative models for the urban planning task.
1 code implementation • 29 Sep 2023 • Ehtesamul Azim, Dongjie Wang, Kunpeng Liu, Wei zhang, Yanjie Fu
Creating an effective representation space is crucial for mitigating the curse of dimensionality, enhancing model generalization, addressing data sparsity, and leveraging classical models more effectively.
1 code implementation • 8 Sep 2023 • Wangyang Ying, Dongjie Wang, Kunpeng Liu, Leilei Sun, Yanjie Fu
Feature generation aims to generate new and meaningful features to create a discriminative representation space. A generated feature is meaningful when the generated feature is from a feature pair with inherent feature interaction.
1 code implementation • 29 Jun 2023 • Meng Xiao, Dongjie Wang, Min Wu, Kunpeng Liu, Hui Xiong, Yuanchun Zhou, Yanjie Fu
Feature transformation aims to reconstruct an effective representation space by mathematically refining the existing features.
no code implementations • 18 May 2023 • Dongjie Wang, Zhengzhang Chen, Yanjie Fu, Yanchi Liu, Haifeng Chen
In this paper, we propose CORAL, a novel online RCA framework that can automatically trigger the RCA process and incrementally update the RCA model.
no code implementations • 8 Apr 2023 • Dongjie Wang, Chang-Tien Lu, Yanjie Fu
The two fields of urban planning and artificial intelligence (AI) arose and developed separately.
no code implementations • 26 Feb 2023 • Meng Xiao, Dongjie Wang, Min Wu, Pengfei Wang, Yuanchun Zhou, Yanjie Fu
Furthermore, we reconstruct feature selection solutions using these embeddings and select the feature subset with the highest performance for downstream tasks as the optimal subset.
1 code implementation • 24 Feb 2023 • Ehtesamul Azim, Dongjie Wang, Yanjie Fu
The temporal embeddings are mapped to the new graph as node attributes to form weighted attributed graph.
1 code implementation • 22 Feb 2023 • Wei Fan, Pengyang Wang, Dongkun Wang, Dongjie Wang, Yuanchun Zhou, Yanjie Fu
The distribution shift in Time Series Forecasting (TSF), indicating series distribution changes over time, largely hinders the performance of TSF models.
no code implementations • 3 Feb 2023 • Dongjie Wang, Zhengzhang Chen, Jingchao Ni, Liang Tong, Zheng Wang, Yanjie Fu, Haifeng Chen
REASON consists of Topological Causal Discovery and Individual Causal Discovery.
1 code implementation • 27 Dec 2022 • Meng Xiao, Dongjie Wang, Min Wu, Ziyue Qiao, Pengfei Wang, Kunpeng Liu, Yuanchun Zhou, Yanjie Fu
Feature transformation for AI is an essential task to boost the effectiveness and interpretability of machine learning (ML).
no code implementations • 25 Dec 2022 • Dongkun Wang, Wei Fan, Pengyang Wang, Pengfei Wang, Dongjie Wang, Denghui Zhang, Yanjie Fu
To tackle the challenge, we propose a generic model for enabling the current traffic speed prediction methods to preserve implicit spatial correlations.
no code implementations • 1 Dec 2022 • Dongjie Wang, Lingfei Wu, Denghui Zhang, Jingbo Zhou, Leilei Sun, Yanjie Fu
The third stage is to leverage multi-attentions to model the zone-zone peer dependencies of the functionality projections to generate grid-level land-use configurations.
no code implementations • 26 Sep 2022 • Dongjie Wang, Kunpeng Liu, Yanyong Huang, Leilei Sun, Bowen Du, Yanjie Fu
While automated urban planners have been examined, they are constrained because of the following: 1) neglecting human requirements in urban planning; 2) omitting spatial hierarchies in urban planning, and 3) lacking numerous urban plan data samples.
no code implementations • 16 Sep 2022 • Meng Xiao, Dongjie Wang, Min Wu, Kunpeng Liu, Hui Xiong, Yuanchun Zhou, Yanjie Fu
Feature transformation aims to extract a good representation (feature) space by mathematically transforming existing features.
no code implementations • 20 Aug 2022 • Yanyong Huang, Zongxin Shen, Yuxin Cai, Xiuwen Yi, Dongjie Wang, Fengmao Lv, Tianrui Li
Besides, learning the complete similarity graph, as an important promising technology in existing MUFS methods, cannot achieve due to the missing views.
no code implementations • 28 May 2022 • Dongjie Wang, Yanjie Fu, Kunpeng Liu, Xiaolin Li, Yan Solihin
We reformulate representation space reconstruction into an interactive process of nested feature generation and selection, where feature generation is to generate new meaningful and explicit features, and feature selection is to eliminate redundant features to control feature sizes.
no code implementations • 13 Mar 2022 • Dongjie Wang, Pengyang Wang, Yanjie Fu, Kunpeng Liu, Hui Xiong, Charles E. Hughes
The profiling framework is formulated into a reinforcement learning task, where an agent is a next-visit planner, an action is a POI that a user will visit next, and the state of the environment is a fused representation of a user and spatial entities.
no code implementations • 19 Jan 2022 • Dongjie Wang, Kunpeng Liu, Hui Xiong, Yanjie Fu
An event that a user visits a POI in stream updates the states of both users and geospatial contexts; the agent perceives the updated environment state to make online recommendations.
no code implementations • 26 Dec 2021 • Dongjie Wang, Yanjie Fu, Kunpeng Liu, Fanglan Chen, Pengyang Wang, Chang-Tien Lu
However, three major challenges arise: 1) how to define a quantitative land-use configuration?
no code implementations • 12 Oct 2021 • Dongjie Wang, Kunpeng Liu, Pauline Johnson, Leilei Sun, Bowen Du, Yanjie Fu
Existing studies usually ignore the need of personalized human guidance in planning, and spatial hierarchical structure in planning generation.
no code implementations • 29 Sep 2021 • Kunpeng Liu, Pengfei Wang, Dongjie Wang, Wan Du, Dapeng Oliver Wu, Yanjie Fu
In this paper, we propose a single-agent Monte Carlo based reinforced feature selection (MCRFS) method, as well as two efficiency improvement strategies, i. e., early stopping (ES) strategy and reward-level interactive (RI) strategy.
no code implementations • 22 Sep 2021 • Dongjie Wang, Kunpeng Liu, David Mohaisen, Pengyang Wang, Chang-Tien Lu, Yanjie Fu
Texts of spatial entities, on the other hand, provide semantic understanding of latent feature labels, but is insensible to deep SRL models.
no code implementations • 7 Jan 2021 • Dongjie Wang, Pengyang Wang, Kunpeng Liu, Yuanchun Zhou, Charles Hughes, Yanjie Fu
To solve the problem, we propose an adversarial training strategy to guarantee the robustness of the representation module.
no code implementations • 26 Aug 2020 • Dongjie Wang, Pengyang Wang, Jingbo Zhou, Leilei Sun, Bowen Du, Yanjie Fu
To this end, we propose a structured anomaly detection framework to defend WTNs by modeling the spatio-temporal characteristics of cyber attacks in WTNs.
no code implementations • 22 Aug 2020 • Dongjie Wang, Yanjie Fu, Pengyang Wang, Bo Huang, Chang-Tien Lu
The objective is then to propose an adversarial learning framework that can automatically generate such tensor for an unplanned area.
no code implementations • 22 Aug 2020 • Dongjie Wang, Yan Yang, Shangming Ning
Urban resource scheduling is an important part of the development of a smart city, and transportation resources are the main components of urban resources.