Search Results for author: Min Zhou

Found 28 papers, 12 papers with code

UNREAL:Unlabeled Nodes Retrieval and Labeling for Heavily-imbalanced Node Classification

no code implementations18 Mar 2023 Liang Yan, Shengzhong Zhang, Bisheng Li, Min Zhou, Zengfeng Huang

To select which unlabeled nodes to add, we propose geometric ranking to rank unlabeled nodes.

Hyperbolic Curvature Graph Neural Network

no code implementations4 Dec 2022 Menglin Yang, Min Zhou, Lujia Pan, Irwin King

To this end, we explore the properties of the local discrete curvature of graph topology and the continuous global curvature of embedding space.

Link Prediction Node Classification +1

Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation

no code implementations15 Nov 2022 Zhihao Zhu, Chenwang Wu, Min Zhou, Hao Liao, Defu Lian, Enhong Chen

Recent studies show that Graph Neural Networks(GNNs) are vulnerable and easily fooled by small perturbations, which has raised considerable concerns for adapting GNNs in various safety-critical applications.

Adversarial Attack

Deep Explainable Learning with Graph Based Data Assessing and Rule Reasoning

no code implementations9 Nov 2022 Yuanlong Li, Gaopan Huang, Min Zhou, Chuan Fu, Honglin Qiao, Yan He

Learning an explainable classifier often results in low accuracy model or ends up with a huge rule set, while learning a deep model is usually more capable of handling noisy data at scale, but with the cost of hard to explain the result and weak at generalization.

Hyperbolic Graph Representation Learning: A Tutorial

no code implementations8 Nov 2022 Min Zhou, Menglin Yang, Lujia Pan, Irwin King

We first give a brief introduction to graph representation learning as well as some preliminary Riemannian and hyperbolic geometry.

Graph Learning Graph Representation Learning +2

Transposed Variational Auto-encoder with Intrinsic Feature Learning for Traffic Forecasting

2 code implementations30 Oct 2022 Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou

In this technical report, we present our solutions to the Traffic4cast 2022 core challenge and extended challenge.

Graph Attention

Geometry Aligned Variational Transformer for Image-conditioned Layout Generation

no code implementations2 Sep 2022 Yunning Cao, Ye Ma, Min Zhou, Chuanbin Liu, Hongtao Xie, Tiezheng Ge, Yuning Jiang

First, self-attention mechanism is adopted to model the contextual relationship within layout elements, while cross-attention mechanism is used to fuse the visual information of conditional images.

Layout Design Object Localization

Towards Learning in Grey Spatiotemporal Systems: A Prophet to Non-consecutive Spatiotemporal Dynamics

no code implementations17 Aug 2022 Zhengyang Zhou, Yang Kuo, Wei Sun, Binwu Wang, Min Zhou, Yunan Zong, Yang Wang

To infer region-wise proximity under flexible factor-wise combinations and enable dynamic neighborhood aggregations, we further disentangle compounded influences of exogenous factors on region-wise proximity and learn to aggregate them.

HICF: Hyperbolic Informative Collaborative Filtering

1 code implementation19 Jul 2022 Menglin Yang, Zhihao LI, Min Zhou, Jiahong Liu, Irwin King

The results reveal that (1) tail items get more emphasis in hyperbolic space than that in Euclidean space, but there is still ample room for improvement; (2) head items receive modest attention in hyperbolic space, which could be considerably improved; (3) and nonetheless, the hyperbolic models show more competitive performance than Euclidean models.

Collaborative Filtering Recommendation Systems

Boosting Factorization Machines via Saliency-Guided Mixup

1 code implementation17 Jun 2022 Chenwang Wu, Defu Lian, Yong Ge, Min Zhou, Enhong Chen, DaCheng Tao

Second, considering that MixFM may generate redundant or even detrimental instances, we further put forward a novel Factorization Machine powered by Saliency-guided Mixup (denoted as SMFM).

Recommendation Systems

Learning-based AC-OPF Solvers on Realistic Network and Realistic Loads

no code implementations19 May 2022 Tsun Ho Aaron Cheung, Min Zhou, Minghua Chen

Deep learning approaches for the Alternating Current-Optimal Power Flow (AC-OPF) problem are under active research in recent years.

Composition-aware Graphic Layout GAN for Visual-textual Presentation Designs

no code implementations30 Apr 2022 Min Zhou, Chenchen Xu, Ye Ma, Tiezheng Ge, Yuning Jiang, Weiwei Xu

Through both quantitative and qualitative evaluations, we demonstrate that the proposed model can synthesize high-quality graphic layouts according to image compositions.

Discovering Representative Attribute-stars via Minimum Description Length

no code implementations27 Apr 2022 Jiahong Liu, Min Zhou, Philippe Fournier-Viger, Menglin Yang, Lujia Pan, Mourad Nouioua

However, there are generally two limitations that hinder their practical use: (1) they have multiple parameters that are hard to set but greatly influence results, (2) and they generally focus on identifying complex subgraphs while ignoring relationships between attributes of nodes. Graphs are a popular data type found in many domains.

Decision Making

BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction

1 code implementation18 Apr 2022 Bisheng Li, Min Zhou, Shengzhong Zhang, Menglin Yang, Defu Lian, Zengfeng Huang

Regarding missing link inference of diverse networks, we revisit the link prediction techniques and identify the importance of both the structural and attribute information.

Graph Classification Link Prediction +1

HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization

1 code implementation18 Apr 2022 Menglin Yang, Min Zhou, Jiahong Liu, Defu Lian, Irwin King

Hyperbolic space offers a spacious room to learn embeddings with its negative curvature and metric properties, which can well fit data with tree-like structures.

Collaborative Filtering Recommendation Systems

TeleGraph: A Benchmark Dataset for Hierarchical Link Prediction

1 code implementation16 Apr 2022 Min Zhou, Bisheng Li, Menglin Yang, Lujia Pan

Link prediction is a key problem for network-structured data, attracting considerable research efforts owing to its diverse applications.

Link Prediction

Hyperbolic Graph Neural Networks: A Review of Methods and Applications

1 code implementation28 Feb 2022 Menglin Yang, Min Zhou, Zhihao LI, Jiahong Liu, Lujia Pan, Hui Xiong, Irwin King

Graph neural networks generalize conventional neural networks to graph-structured data and have received widespread attention due to their impressive representation ability.

Anatomy Graph Learning

Enhancing Hyperbolic Graph Embeddings via Contrastive Learning

no code implementations21 Jan 2022 Jiahong Liu, Menglin Yang, Min Zhou, Shanshan Feng, Philippe Fournier-Viger

Inspired by the recently active and emerging self-supervised learning, in this study, we attempt to enhance the representation power of hyperbolic graph models by drawing upon the advantages of contrastive learning.

Contrastive Learning Graph Representation Learning +2

Boosting Image Outpainting with Semantic Layout Prediction

no code implementations18 Oct 2021 Ye Ma, Jin Ma, Min Zhou, Quan Chen, Tiezheng Ge, Yuning Jiang, Tong Lin

Secondly, another GAN model is trained to synthesize real images based on the extended semantic layouts.

Image Outpainting Semantic Segmentation

Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space

1 code implementation8 Jul 2021 Menglin Yang, Min Zhou, Marcus Kalander, Zengfeng Huang, Irwin King

To explore these properties of a complex temporal network, we propose a hyperbolic temporal graph network (HTGN) that fully takes advantage of the exponential capacity and hierarchical awareness of hyperbolic geometry.

Graph Embedding Link Prediction +1

Scaling Up Graph Neural Networks Via Graph Coarsening

1 code implementation9 Jun 2021 Zengfeng Huang, Shengzhong Zhang, Chong Xi, Tang Liu, Min Zhou

Scalability of graph neural networks remains one of the major challenges in graph machine learning.

Stochastic Optimization

An Influence-based Approach for Root Cause Alarm Discovery in Telecom Networks

1 code implementation7 May 2021 Keli Zhang, Marcus Kalander, Min Zhou, Xi Zhang, Junjian Ye

Alarm root cause analysis is a significant component in the day-to-day telecommunication network maintenance, and it is critical for efficient and accurate fault localization and failure recovery.

Causal Inference Fault localization +2

Spatio-Temporal Hybrid Graph Convolutional Network for Traffic Forecasting in Telecommunication Networks

no code implementations17 Sep 2020 Marcus Kalander, Min Zhou, Chengzhi Zhang, Hanling Yi, Lujia Pan

We conduct extensive experiments on real-world traffic datasets collected from telecommunication networks.

Imbalanced classification: a paradigm-based review

no code implementations11 Feb 2020 Yang Feng, Min Zhou, Xin Tong

For each pair of resampling techniques and classification methods, we use simulation studies and a real data set on credit card fraud to study the performance under different evaluation metrics.

Classification General Classification +1

BOLT-SSI: A Statistical Approach to Screening Interaction Effects for Ultra-High Dimensional Data

1 code implementation10 Feb 2019 Min Zhou, Mingwei Dai, Yuan YAO, Jin Liu, Can Yang, Heng Peng

In this paper, we first propose a simple method for sure screening interactions (SSI).


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