b'Pan Li'

research

∙ 08/17/2023

Optimal Resource Allocation for U-Shaped Parallel Split Learning

Split learning (SL) has emerged as a promising approach for model traini...

0 Song Lyu, et al. ∙

research

∙ 07/12/2023

Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection

Graph learning methods, such as Graph Neural Networks (GNNs) based on gr...

0 Eli Chien, et al. ∙

research

∙ 06/04/2023

Less is More: Revisiting Gaussian Mechanism for Differential Privacy

In this paper, we identify that the classic Gaussian mechanism and its v...

0 Tianxi Ji, et al. ∙

research

∙ 06/02/2023

GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction

Graph Anomaly Detection (GAD) is a technique used to identify abnormal n...

1 Amit Roy, et al. ∙

research

∙ 04/22/2023

Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities

Smart cities demand resources for rich immersive sensing, ubiquitous com...

0 Xianhao Chen, et al. ∙

research

∙ 04/20/2023

Improving Graph Neural Networks on Multi-node Tasks with Labeling Tricks

In this paper, we provide a theory of using graph neural networks (GNNs)...

0 Xiyuan Wang, et al. ∙

research

∙ 03/06/2023

SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning

Subgraph-based graph representation learning (SGRL) has recently emerged...

0 Haoteng Yin, et al. ∙

research

∙ 01/08/2023

Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning

A general framework of unsupervised learning for combinatorial optimizat...

0 Haoyu Wang, et al. ∙

research

∙ 12/23/2022

Graph Federated Learning with Hidden Representation Sharing

Learning on Graphs (LoG) is widely used in multi-client systems when eac...

2 Shuang Wu, et al. ∙

research

∙ 10/30/2022

Interpretable Geometric Deep Learning via Learnable Randomness Injection

Point cloud data is ubiquitous in scientific fields. Recently, geometric...

13 Siqi Miao, et al. ∙

research

∙ 10/27/2022

Federated Graph Representation Learning using Self-Supervision

Federated graph representation learning (FedGRL) brings the benefits of ...

0 Susheel Suresh, et al. ∙

research

∙ 10/17/2022

Extensible Proxy for Efficient NAS

Neural Architecture Search (NAS) has become a de facto approach in the r...

0 Yuhong Li, et al. ∙

research

∙ 10/17/2022

A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information

Unlike traditional static deep neural networks (DNNs), dynamic neural ne...

1 Pan Li, et al. ∙

research

∙ 09/08/2022

SSL-WM: A Black-Box Watermarking Approach for Encoders Pre-trained by Self-supervised Learning

Recent years have witnessed significant success in Self-Supervised Learn...

8 Peizhuo Lv, et al. ∙

research

∙ 09/02/2022

Neighborhood-aware Scalable Temporal Network Representation Learning

Temporal networks have been widely used to model real-world complex syst...

2 Yuhong Luo, et al. ∙

research

∙ 07/22/2022

Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective

Graph neural networks (GNNs) have shown superiority in many prediction t...

28 Rongzhe Wei, et al. ∙

research

∙ 07/13/2022

Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation

Using machine learning to solve combinatorial optimization (CO) problems...

11 Haoyu Wang, et al. ∙

research

∙ 06/20/2022

Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction

Link prediction is one important application of graph neural networks (G...

11 Yang Hu, et al. ∙

research

∙ 04/04/2022

Robust Fingerprinting of Genomic Databases

Database fingerprinting has been widely used to discourage unauthorized ...

0 Tianxi Ji, et al. ∙

research

∙ 03/28/2022

A Framework of Meta Functional Learning for Regularising Knowledge Transfer

Machine learning classifiers' capability is largely dependent on the sca...

7 Pan Li, et al. ∙

research

∙ 03/01/2022

Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks

Graph neural networks (GNN) have shown great advantages in many graph-ba...

2 Haorui Wang, et al. ∙

research

∙ 02/28/2022

Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning

Subgraph-based graph representation learning (SGRL) has been recently pr...

3 Haoteng Yin, et al. ∙

research

∙ 02/18/2022

Graph Auto-Encoder Via Neighborhood Wasserstein Reconstruction

Graph neural networks (GNNs) have drawn significant research attention r...

6 Mingyue Tang, et al. ∙

research

∙ 01/31/2022

Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism

Interpretable graph learning is in need as many scientific applications ...

13 Siqi Miao, et al. ∙

research

∙ 01/25/2022

Energy-Efficient Computation Offloading in MobileEdge Computing Systems with Uncertainties

Computation offloading is indispensable for mobile edge computing (MEC)....

0 Tianxi Ji, et al. ∙

research

∙ 01/18/2022

High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing

Agile hardware development requires fast and accurate circuit quality ev...

6 Nan Wu, et al. ∙

research

∙ 12/01/2021

Ranking Distance Calibration for Cross-Domain Few-Shot Learning

Recent progress in few-shot learning promotes a more realistic cross-dom...

0 Pan Li, et al. ∙

research

∙ 10/25/2021

Nested Graph Neural Networks

Graph neural network (GNN)'s success in graph classification is closely ...

0 Muhan Zhang, et al. ∙

research

∙ 09/13/2021

Program-to-Circuit: Exploiting GNNs for Program Representation and Circuit Translation

Circuit design is complicated and requires extensive domain-specific exp...

6 Nan Wu, et al. ∙

research

∙ 09/06/2021

Differentially-Private Fingerprinting of Relational Databases

When sharing sensitive databases with other parties, a database owner ai...

0 Tianxi Ji, et al. ∙

research

∙ 08/04/2021

Generic Neural Architecture Search via Regression

Most existing neural architecture search (NAS) algorithms are dedicated ...

0 Yuhong Li, et al. ∙

research

∙ 07/03/2021

On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs

Graph neural networks (GNNs) have been widely used in various graph-rela...

0 Hejie Cui, et al. ∙

research

∙ 06/11/2021

Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns

Graph neural networks (GNNs) have achieved tremendous success on multipl...

0 Susheel Suresh, et al. ∙

research

∙ 06/10/2021

Neural Higher-order Pattern (Motif) Prediction in Temporal Networks

Dynamic systems that consist of a set of interacting elements can be abs...

0 Yunyu Liu, et al. ∙

research

∙ 06/10/2021

Adversarial Graph Augmentation to Improve Graph Contrastive Learning

Self-supervised learning of graph neural networks (GNN) is in great need...

0 Susheel Suresh, et al. ∙

research

∙ 06/08/2021

Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks

Hypergraph offers a framework to depict the multilateral relationships i...

0 Changlin Wan, et al. ∙

research

∙ 06/05/2021

PURS: Personalized Unexpected Recommender System for Improving User Satisfaction

Classical recommender system methods typically face the filter bubble pr...

0 Pan Li, et al. ∙

research

∙ 06/05/2021

Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction

Cross domain recommender system constitutes a powerful method to tackle ...

0 Pan Li, et al. ∙

research

∙ 04/17/2021

Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations

Cross domain recommender systems have been increasingly valuable for hel...

6 Pan Li, et al. ∙

research

∙ 04/13/2021

MELOPPR: Software/Hardware Co-design for Memory-efficient Low-latency Personalized PageRank

Personalized PageRank (PPR) is a graph algorithm that evaluates the impo...

0 Lixiang Li, et al. ∙

research

∙ 03/11/2021

The Curse of Correlations for Robust Fingerprinting of Relational Databases

Database fingerprinting schemes have been widely adopted to prevent unau...

0 Tianxi Ji, et al. ∙

research

∙ 02/15/2021

Genomic Data Sharing under Dependent Local Differential Privacy

Privacy-preserving genomic data sharing is prominent to increase the pac...

0 Emre Yilmaz, et al. ∙

research

∙ 01/15/2021

Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks

Temporal networks serve as abstractions of many real-world dynamic syste...

6 Yanbang Wang, et al. ∙

research

∙ 01/06/2021

Handling many conversions per click in modeling delayed feedback

Predicting the expected value or number of post-click conversions (purch...

0 Ashwinkumar Badanidiyuru, et al. ∙

research

∙ 11/22/2020

Revisiting graph neural networks and distance encoding in a practical view

Graph neural networks (GNNs) are widely used in the applications based o...

0 Haoteng Yin, et al. ∙

research

∙ 11/09/2020

F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams

Edge streams are commonly used to capture interactions in dynamic networ...

8 Yen-Yu Chang, et al. ∙

research

∙ 10/30/2020

Revisiting Graph Neural Networks for Link Prediction

Graph neural networks (GNNs) have achieved great success in recent years...

0 Muhan Zhang, et al. ∙

research

∙ 10/24/2020

Graph Information Bottleneck

Representation learning of graph-structured data is challenging because ...

20 Tailin Wu, et al. ∙

research

∙ 09/17/2020

MStream: Fast Streaming Multi-Aspect Group Anomaly Detection

Given a stream of entries in a multi-aspect data setting i.e., entries h...

18 Siddharth Bhatia, et al. ∙

research

∙ 08/31/2020

Distance Encoding – Design Provably More Powerful Graph Neural Networks for Structural Representation Learning

Learning structural representations of node sets from graph-structured d...

42 Pan Li, et al. ∙

Pan Li

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