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


Jan 18, 2022
Nan Wu, Hang Yang, Yuan Xie, Pan Li, Cong Hao


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Ranking Distance Calibration for Cross-Domain Few-Shot Learning


Dec 01, 2021
Pan Li, Shaogang Gong, Yanwei Fu, Chengjie Wang


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Nested Graph Neural Networks


Oct 25, 2021
Muhan Zhang, Pan Li

* Accepted to NeurIPS 2021 

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Applications and Techniques for Fast Machine Learning in Science


Oct 25, 2021
Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bahr, Jurgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomas E. Muller Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Kyle J Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng

* 66 pages, 13 figures, 5 tables 

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


Sep 13, 2021
Nan Wu, Huake He, Yuan Xie, Pan Li, Cong Hao


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Generic Neural Architecture Search via Regression


Aug 04, 2021
Yuhong Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen


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


Jul 03, 2021
Hejie Cui, Zijie Lu, Pan Li, Carl Yang

* This paper has been accepted to the Sixth International Workshop on Deep Learning on Graphs (DLG-KDD'21) (co-located with KDD'21) 

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Adversarial Graph Augmentation to Improve Graph Contrastive Learning


Jun 25, 2021
Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville

* link to code is added (https://github.com/susheels/adgcl

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Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks


Jun 13, 2021
Changlin Wan, Muhan Zhang, Wei Hao, Sha Cao, Pan Li, Chi Zhang


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


Jun 11, 2021
Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma

* published in KDD 2021; 11 pages; 

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


Jun 10, 2021
Yunyu Liu, Jianzhu Ma, Pan Li


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PURS: Personalized Unexpected Recommender System for Improving User Satisfaction


Jun 05, 2021
Pan Li, Maofei Que, Zhichao Jiang, Yao Hu, Alexander Tuzhilin

* Accepted to RecSys20 

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


Jun 05, 2021
Pan Li, Zhichao Jiang, Maofei Que, Yao Hu, Alexander Tuzhilin

* Accepted to KDD21 

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Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations


Apr 20, 2021
Pan Li, Alexander Tuzhilin

* Accepted to IEEE TKDE. arXiv admin note: text overlap with arXiv:1910.05189 

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HufuNet: Embedding the Left Piece as Watermark and Keeping the Right Piece for Ownership Verification in Deep Neural Networks


Mar 25, 2021
Peizhuo Lv, Pan Li, Shengzhi Zhang, Kai Chen, Ruigang Liang, Yue Zhao, Yingjiu Li


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Local Hyper-flow Diffusion


Mar 08, 2021
Kimon Fountoulakis, Pan Li, Shenghao Yang

* 36 pages, 2 figures, 9 tables 

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Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks


Jan 15, 2021
Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li

* Accepted to ICLR 2021 

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Handling many conversions per click in modeling delayed feedback


Jan 06, 2021
Ashwinkumar Badanidiyuru, Andrew Evdokimov, Vinodh Krishnan, Pan Li, Wynn Vonnegut, Jayden Wang


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Revisiting graph neural networks and distance encoding from a practical view


Nov 29, 2020
Haoteng Yin, Yanbang Wang, Pan Li


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


Nov 09, 2020
Yen-Yu Chang, Pan Li, Rok Sosic, M. H. Afifi, Marco Schweighauser, Jure Leskovec

* WSDM 2021 

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Revisiting Graph Neural Networks for Link Prediction


Oct 30, 2020
Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin


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Graph Information Bottleneck


Oct 24, 2020
Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec

* 20 pages, 3 figures, NeurIPS 2020 

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MStream: Fast Streaming Multi-Aspect Group Anomaly Detection


Sep 17, 2020
Siddharth Bhatia, Arjit Jain, Pan Li, Ritesh Kumar, Bryan Hooi


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


Sep 05, 2020
Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec


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