Search Results for author: Yanjie Fu

Found 56 papers, 17 papers with code

Disentangled Causal Graph Learning forOnline Unsupervised Root Cause Analysis

no code implementations18 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.

Graph Learning

Locate and Beamform: Two-dimensional Locating All-neural Beamformer for Multi-channel Speech Separation

no code implementations18 May 2023 Yanjie Fu, Meng Ge, Honglong Wang, Nan Li, Haoran Yin, Longbiao Wang, Gaoyan Zhang, Jianwu Dang, Chengyun Deng, Fei Wang

Recently, stunning improvements on multi-channel speech separation have been achieved by neural beamformers when direction information is available.

Speech Separation

Adaptive Path-Memory Network for Temporal Knowledge Graph Reasoning

no code implementations25 Apr 2023 Hao Dong, Zhiyuan Ning, Pengyang Wang, Ziyue Qiao, Pengfei Wang, Yuanchun Zhou, Yanjie Fu

Temporal knowledge graph (TKG) reasoning aims to predict the future missing facts based on historical information and has gained increasing research interest recently.

Towards Automated Urban Planning: When Generative and ChatGPT-like AI Meets Urban Planning

no code implementations8 Apr 2023 Dongjie Wang, Chang-Tien Lu, Yanjie Fu

The two fields of urban planning and artificial intelligence (AI) arose and developed separately.

Data-Centric AI: Deep Generative Differentiable Feature Selection via Discrete Subsetting as Continuous Embedding Space Optimization

no code implementations26 Feb 2023 Meng Xiao, Dongjie Wang, Min Wu, Pengfei Wang, Yuanchun Zhou, Yanjie Fu

We generalize this problem into a deep differentiable feature selection task and propose a new perspective: discrete feature subsetting as continuous embedding space optimization.

feature selection

Deep Graph Stream SVDD: Anomaly Detection in Cyber-Physical Systems

1 code implementation24 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.

Anomaly Detection

Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting

1 code implementation22 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.

Time Series Forecasting

PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation

1 code implementation20 Feb 2023 Mingzhe Liu, Han Huang, Hao Feng, Leilei Sun, Bowen Du, Yanjie Fu

Our proposed framework provides a conditional feature extraction module first to extract the coarse yet effective spatiotemporal dependencies from conditional information as the global context prior.

Imputation Noise Estimation

Traceable Automatic Feature Transformation via Cascading Actor-Critic Agents

1 code implementation27 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).

feature selection

Boosting Urban Traffic Speed Prediction via Integrating Implicit Spatial Correlations

no code implementations25 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.

Human-instructed Deep Hierarchical Generative Learning for Automated Urban Planning

no code implementations1 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.

Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective

no code implementations31 Oct 2022 Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Lim Ee Peng, Yanjie Fu

We present a gradient perspective to understand two negative impacts of popularity bias in recommendation model optimization: (i) the gradient direction of popular item embeddings is closer to that of positive interactions, and (ii) the magnitude of positive gradient for popular items are much greater than that of unpopular items.

Model Optimization Recommendation Systems

Kernel-based Substructure Exploration for Next POI Recommendation

1 code implementation8 Oct 2022 Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, Ming Zhang

To tackle the above issues, we propose a Kernel-Based Graph Neural Network (KBGNN) for next POI recommendation, which combines the characteristics of both geographical and sequential influences in a collaborative way.

Recommendation Systems

Automated Urban Planning aware Spatial Hierarchies and Human Instructions

no code implementations26 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.

Self-Optimizing Feature Transformation

no code implementations16 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.

Feature Engineering Outlier Detection

Hierarchical Interdisciplinary Topic Detection Model for Research Proposal Classification

no code implementations16 Sep 2022 Meng Xiao, Ziyue Qiao, Yanjie Fu, Hao Dong, Yi Du, Pengyang Wang, Hui Xiong, Yuanchun Zhou

Specifically, we first propose a hierarchical transformer to extract the textual semantic information of proposals.


MIMO-DoAnet: Multi-channel Input and Multiple Outputs DoA Network with Unknown Number of Sound Sources

1 code implementation15 Jul 2022 Haoran Yin, Meng Ge, Yanjie Fu, Gaoyan Zhang, Longbiao Wang, Lei Zhang, Lin Qiu, Jianwu Dang

These algorithms are usually achieved by mapping the multi-channel audio input to the single output (i. e. overall spatial pseudo-spectrum (SPS) of all sources), that is called MISO.

Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction

1 code implementation30 Jun 2022 Liangzhe Han, Xiaojian Ma, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv, Hui Xiong

Traffic demand forecasting by deep neural networks has attracted widespread interest in both academia and industry society.

Graph Representation Learning

Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting

1 code implementation28 Jun 2022 Junchen Ye, Zihan Liu, Bowen Du, Leilei Sun, Weimiao Li, Yanjie Fu, Hui Xiong

To equip the graph neural network with a flexible and practical graph structure, in this paper, we investigate how to model the evolutionary and multi-scale interactions of time series.

Multivariate Time Series Forecasting Self-Learning

Iterative Sound Source Localization for Unknown Number of Sources

2 code implementations24 Jun 2022 Yanjie Fu, Meng Ge, Haoran Yin, Xinyuan Qian, Longbiao Wang, Gaoyan Zhang, Jianwu Dang

Sound source localization aims to seek the direction of arrival (DOA) of all sound sources from the observed multi-channel audio.

Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction

no code implementations28 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.

Feature Engineering feature selection +1

Semi-supervised Drifted Stream Learning with Short Lookback

no code implementations25 May 2022 Weijieying Ren, Pengyang Wang, Xiaolin Li, Charles E. Hughes, Yanjie Fu

In many scenarios, 1) data streams are generated in real time; 2) labeled data are expensive and only limited labels are available in the beginning; 3) real-world data is not always i. i. d.

Domain Adaptation Pseudo Label

DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting

1 code implementation ICLR 2022 Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu

However, the complicated dependencies of the PTS signal on its inherent periodicity as well as the sophisticated composition of various periods hinder the performance of PTS forecasting.

Scheduling Time Series Forecasting

Reinforced Imitative Graph Learning for Mobile User Profiling

no code implementations13 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.

Graph Learning

Who Should Review Your Proposal? Interdisciplinary Topic Path Detection for Research Proposals

no code implementations7 Mar 2022 Meng Xiao, Ziyue Qiao, Yanjie Fu, Hao Dong, Yi Du, Pengyang Wang, Dong Li, Yuanchun Zhou

After extracting the semantic and interdisciplinary knowledge, we design a level-wise prediction component to fuse the two types of knowledge representations and detect interdisciplinary topic paths for each proposal.

Online POI Recommendation: Learning Dynamic Geo-Human Interactions in Streams

no code implementations19 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.

reinforcement-learning Reinforcement Learning (RL)

Deep Human-guided Conditional Variational Generative Modeling for Automated Urban Planning

no code implementations12 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.

Image Generation

Efficient Reinforced Feature Selection via Early Stopping Traverse Strategy

no code implementations29 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.

feature selection

Automated Feature-Topic Pairing: Aligning Semantic and Embedding Spaces in Spatial Representation Learning

no code implementations22 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.

Representation Learning

Democratizing Evaluation of Deep Model Interpretability through Consensus

no code implementations1 Jan 2021 Xuhong LI, Haoyi Xiong, Siyu Huang, Shilei Ji, Yanjie Fu, Dejing Dou

Given any task/dataset, Consensus first obtains the interpretation results using existing tools, e. g., LIME (Ribeiro et al., 2016), for every model in the committee, then aggregates the results from the entire committee and approximates the “ground truth” of interpretations through voting.

Feature Importance

Coupled Layer-wise Graph Convolution for Transportation Demand Prediction

1 code implementation15 Dec 2020 Junchen Ye, Leilei Sun, Bowen Du, Yanjie Fu, Hui Xiong

Graph Convolutional Network (GCN) has been widely applied in transportation demand prediction due to its excellent ability to capture non-Euclidean spatial dependence among station-level or regional transportation demands.

Interactive Reinforcement Learning for Feature Selection with Decision Tree in the Loop

no code implementations2 Oct 2020 Wei Fan, Kunpeng Liu, Hao liu, Yong Ge, Hui Xiong, Yanjie Fu

In this journal version, we propose a novel interactive and closed-loop architecture to simultaneously model interactive reinforcement learning (IRL) and decision tree feedback (DTF).

Feature Importance feature selection +2

Simplifying Reinforced Feature Selection via Restructured Choice Strategy of Single Agent

no code implementations19 Sep 2020 Xiaosa Zhao, Kunpeng Liu, Wei Fan, Lu Jiang, Xiaowei Zhao, Minghao Yin, Yanjie Fu

To address the question, we develop a single-agent reinforced feature selection approach integrated with restructured choice strategy.

feature selection

Learning Adaptive Embedding Considering Incremental Class

1 code implementation31 Aug 2020 Yang Yang, Zhen-Qiang Sun, HengShu Zhu, Yanjie Fu, Hui Xiong, Jian Yang

To this end, we propose a Class-Incremental Learning without Forgetting (CILF) framework, which aims to learn adaptive embedding for processing novel class detection and model update in a unified framework.

class-incremental learning Class Incremental Learning +1

Defending Water Treatment Networks: Exploiting Spatio-temporal Effects for Cyber Attack Detection

no code implementations26 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.

Anomaly Detection Cyber Attack Detection +1

Tree Structure-Aware Graph Representation Learning via Integrated Hierarchical Aggregation and Relational Metric Learning

1 code implementation23 Aug 2020 Ziyue Qiao, Pengyang Wang, Yanjie Fu, Yi Du, Pengfei Wang, Yuanchun Zhou

The integrated hierarchical aggregation module aims to preserve the tree structure by combining GNN with Gated Recurrent Unit to integrate the hierarchical and sequential neighborhood information on the tree structure to node representations.

Graph Representation Learning Metric Learning

Reimagining City Configuration: Automated Urban Planning via Adversarial Learning

no code implementations22 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.

Polestar: An Intelligent, Efficient and National-Wide Public Transportation Routing Engine

no code implementations11 Jul 2020 Hao Liu, Ying Li, Yanjie Fu, Huaibo Mei, Jingbo Zhou, Xu Ma, Hui Xiong

Then, we introduce a general route search algorithm coupled with an efficient station binding method for efficient route candidate generation.

A Neural Influence Diffusion Model for Social Recommendation

2 code implementations20 Apr 2019 Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang, Meng Wang

The key idea of our proposed model is that we design a layer-wise influence propagation structure to model how users' latent embeddings evolve as the social diffusion process continues.

Collaborative Filtering Recommendation Systems

SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation

no code implementations7 Nov 2018 Le Wu, Peijie Sun, Richang Hong, Yanjie Fu, Xiting Wang, Meng Wang

Based on a classical CF model, the key idea of our proposed model is that we borrow the strengths of GCNs to capture how users' preferences are influenced by the social diffusion process in social networks.

Collaborative Filtering Recommendation Systems

A Hierarchical Attention Model for Social Contextual Image Recommendation

1 code implementation3 Jun 2018 Le Wu, Lei Chen, Richang Hong, Yanjie Fu, Xing Xie, Meng Wang

After that, we design a hierarchical attention network that naturally mirrors the hierarchical relationship (elements in each aspects level, and the aspect level) of users' latent interests with the identified key aspects.

BL-MNE: Emerging Heterogeneous Social Network Embedding through Broad Learning with Aligned Autoencoder

no code implementations26 Nov 2017 Jiawei Zhang, Congying Xia, Chenwei Zhang, Limeng Cui, Yanjie Fu, Philip S. Yu

The closeness among users in the networks are defined as the meta proximity scores, which will be fed into DIME to learn the embedding vectors of users in the emerging network.

Social and Information Networks Databases

CSWA: Aggregation-Free Spatial-Temporal Community Sensing

no code implementations15 Nov 2017 Jiang Bian, Haoyi Xiong, Yanjie Fu, Sajal K. Das

In this paper, we present a novel community sensing paradigm -- {C}ommunity {S}ensing {W}ithout {A}ggregation}.

Compressive Sensing Distributed Optimization

REMIX: Automated Exploration for Interactive Outlier Detection

no code implementations17 May 2017 Yanjie Fu, Charu Aggarwal, Srinivasan Parthasarathy, Deepak S. Turaga, Hui Xiong

This formulation incorporates multiple aspects such as (i) an upper limit on the total execution time of detectors (ii) diversity in the space of algorithms and features, and (iii) meta-learning for evaluating the cost and utility of detectors.

Meta-Learning Outlier Detection

Heterogeneous Metric Learning with Content-based Regularization for Software Artifact Retrieval

no code implementations25 Sep 2014 Liang Wu, Hui Xiong, Liang Du, Bo Liu, Guandong Xu, Yong Ge, Yanjie Fu, Yuanchun Zhou, Jianhui Li

Specifically, this method can capture both the inherent information in the source codes and the semantic information hidden in the comments, descriptions, and identifiers of the source codes.

Information Retrieval Metric Learning +1

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