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ORCIDXiaowen Dong 0001
Person information
- affiliation: University of Oxford, UK
- affiliation (former): IBM Research, Dublin, Ireland
- affiliation (PhD 2014): Swiss Federal Institute of Technology, Lausanne, Switzerland
Other persons with the same name
- Xiaowen Dong 0002
![[0000-0003-4780-1991]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-4780-1991")
(aka: Xiao-Wen Dong 0002) — University of Science and Technology of China, School of Mathematical Sciences, Hefei, China - Xiaowen Dong 0003 — Huawei Technologies, Shenzhen, China (and 1 more)
- Xiaowen Dong 0004 — University of Cambridge, UK
- Xiaowen Dong 0005 — Beijing University of Posts and Telecommunications, School of Electrical and Electronic Engineering, China
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2020 – today
- 2024
[j21]Yan Leng, Xiaowen Dong, Esteban Moro, Alex Pentland:
Long-Range Social Influence in Phone Communication Networks on Offline Adoption Decisions. Inf. Syst. Res. 35(1): 318-338 (2024)- [j20]Déborah Sulem, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong:
Graph similarity learning for change-point detection in dynamic networks. Mach. Learn. 113(1): 1-44 (2024) - [c32]Isabelle Lorge, Li Zhang, Xiaowen Dong, Janet B. Pierrehumbert:
STEntConv: Predicting Disagreement between Reddit Users with Stance Detection and a Signed Graph Convolutional Network. LREC/COLING 2024: 15273-15284 - [c31]Zexi Liu, Bohan Tang, Ziyuan Ye, Xiaowen Dong, Siheng Chen, Yanfeng Wang:
Hypergraph Transformer for Semi-Supervised Classification. ICASSP 2024: 7515-7519 - [c30]Bohan Tang, Siheng Chen, Xiaowen Dong:
Hypergraph-Mlp: Learning on Hypergraphs Without Message Passing. ICASSP 2024: 13476-13480 - [c29]Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin:
A Characterization Theorem for Equivariant Networks with Point-wise Activations. ICLR 2024 - [i62]Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin:
A Characterization Theorem for Equivariant Networks with Point-wise Activations. CoRR abs/2401.09235 (2024) - [i61]Bohan Tang, Zexi Liu, Keyue Jiang, Siheng Chen, Xiaowen Dong:
Hypergraph Node Classification With Graph Neural Networks. CoRR abs/2402.05569 (2024) - [i60]Shuo Tang, Rui Ye, Chenxin Xu, Xiaowen Dong, Siheng Chen, Yanfeng Wang:
Decentralized and Lifelong-Adaptive Multi-Agent Collaborative Learning. CoRR abs/2403.06535 (2024) - [i59]Fernando Moreno-Pino, Alvaro Arroyo, Harrison Waldon, Xiaowen Dong, Álvaro Cartea:
Rough Transformers for Continuous and Efficient Time-Series Modelling. CoRR abs/2403.10288 (2024) - [i58]Isabelle Lorge, Li Zhang, Xiaowen Dong, Janet B. Pierrehumbert:
STEntConv: Predicting Disagreement with Stance Detection and a Signed Graph Convolutional Network. CoRR abs/2403.15885 (2024) - [i57]Mihai Cucuringu, Xiaowen Dong, Ning Zhang:
Maximum Likelihood Estimation on Stochastic Blockmodels for Directed Graph Clustering. CoRR abs/2403.19516 (2024) - [i56]Huidong Liang, Xingchen Wan, Xiaowen Dong:
Bayesian Optimization of Functions over Node Subsets in Graphs. CoRR abs/2405.15119 (2024) - [i55]Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein:
Bundle Neural Networks for message diffusion on graphs. CoRR abs/2405.15540 (2024) - [i54]Fernando Moreno-Pino, Alvaro Arroyo, Harrison Waldon, Xiaowen Dong, Álvaro Cartea:
Rough Transformers: Lightweight Continuous-Time Sequence Modelling with Path Signatures. CoRR abs/2405.20799 (2024) - [i53]Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin:
Separation Power of Equivariant Neural Networks. CoRR abs/2406.08966 (2024) - [i52]Yuqi Nie, Yaxuan Kong, Xiaowen Dong, John M. Mulvey, H. Vincent Poor, Qingsong Wen, Stefan Zohren:
A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges. CoRR abs/2406.11903 (2024) - [i51]Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein:
On the Impact of Sample Size in Reconstructing Noisy Graph Signals: A Theoretical Characterisation. CoRR abs/2406.16816 (2024) - [i50]Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein:
Neural Spacetimes for DAG Representation Learning. CoRR abs/2408.13885 (2024) - 2023
- [j19]Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu:
Local2Global: a distributed approach for scaling representation learning on graphs. Mach. Learn. 112(5): 1663-1692 (2023) - [j18]Yin-Cong Zhi, Yin Cheng Ng, Xiaowen Dong:
Gaussian Processes on Graphs Via Spectral Kernel Learning. IEEE Trans. Signal Inf. Process. over Networks 9: 304-314 (2023) - [c28]Bohan Tang, Siheng Chen, Xiaowen Dong:
Learning Hypergraphs From Signals With Dual Smoothness Prior. ICASSP 2023: 1-5 - [c27]Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni:
DRew: Dynamically Rewired Message Passing with Delay. ICML 2023: 12252-12267 - [c26]Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong:
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization. NeurIPS 2023 - [c25]Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong:
Bayesian Optimisation of Functions on Graphs. NeurIPS 2023 - [c24]Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong:
Graph classification Gaussian processes via spectral features. UAI 2023: 1575-1585 - [c23]Pierre Osselin, Henry Kenlay, Xiaowen Dong:
Structure-aware robustness certificates for graph classification. UAI 2023: 1596-1605 - [i49]Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni:
DRew: Dynamically Rewired Message Passing with Delay. CoRR abs/2305.08018 (2023) - [i48]Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong:
Graph Classification Gaussian Processes via Spectral Features. CoRR abs/2306.03770 (2023) - [i47]Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong:
Bayesian Optimisation of Functions on Graphs. CoRR abs/2306.05304 (2023) - [i46]Pierre Osselin, Henry Kenlay, Xiaowen Dong:
Structure-Aware Robustness Certificates for Graph Classification. CoRR abs/2306.11915 (2023) - [i45]Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein:
On the Impact of Sample Size in Reconstructing Graph Signals. CoRR abs/2307.00336 (2023) - [i44]Chao Zhang, Xingyue Pu, Mihai Cucuringu, Xiaowen Dong:
Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects. CoRR abs/2308.01419 (2023) - [i43]Xingyue Pu, Stephen J. Roberts, Xiaowen Dong, Stefan Zohren:
Network Momentum across Asset Classes. CoRR abs/2308.11294 (2023) - [i42]Xingyue Pu, Stefan Zohren, Stephen J. Roberts, Xiaowen Dong:
Learning to Learn Financial Networks for Optimising Momentum Strategies. CoRR abs/2308.12212 (2023) - [i41]Bohan Tang, Siheng Chen, Xiaowen Dong:
Hypergraph Structure Inference From Data Under Smoothness Prior. CoRR abs/2308.14172 (2023) - [i40]Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong:
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization. CoRR abs/2309.04810 (2023) - [i39]Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong:
Gromov-Hausdorff Distances for Comparing Product Manifolds of Model Spaces. CoRR abs/2309.05678 (2023) - [i38]Bohan Tang, Siheng Chen, Xiaowen Dong:
Hypergraph-MLP: Learning on Hypergraphs without Message Passing. CoRR abs/2312.09778 (2023) - [i37]Zexi Liu, Bohan Tang, Ziyuan Ye, Xiaowen Dong, Siheng Chen, Yanfeng Wang:
Hypergraph Transformer for Semi-Supervised Classification. CoRR abs/2312.11385 (2023) - 2022
- [j17]Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael A. Osborne, Stephen J. Roberts:
Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms 15(6): 209 (2022) - [c22]Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong:
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. AISTATS 2022: 4818-4834 - [c21]Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
Understanding over-squashing and bottlenecks on graphs via curvature. ICLR 2022 - [c20]Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong:
Learning to Infer Structures of Network Games. ICML 2022: 18809-18827 - [c19]Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs With Missing Node Features. LoG 2022: 11 - [c18]Valentin Hofmann, Xiaowen Dong, Janet B. Pierrehumbert, Hinrich Schütze:
Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity. NAACL-HLT (Findings) 2022: 536-550 - [i36]Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu:
Local2Global: A distributed approach for scaling representation learning on graphs. CoRR abs/2201.04729 (2022) - [i35]Déborah Sulem, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong:
Graph similarity learning for change-point detection in dynamic networks. CoRR abs/2203.15470 (2022) - [i34]Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong:
Learning to Infer Structures of Network Games. CoRR abs/2206.08119 (2022) - [i33]Enpei Zhang, Shuo Tang, Xiaowen Dong, Siheng Chen, Yanfeng Wang:
Unrolled Graph Learning for Multi-Agent Collaboration. CoRR abs/2210.17101 (2022) - [i32]Bohan Tang, Siheng Chen, Xiaowen Dong:
Learning Hypergraphs From Signals With Dual Smoothness Prior. CoRR abs/2211.01717 (2022) - [i31]Yin-Cong Zhi, Felix L. Opolka, Yin Cheng Ng, Pietro Liò, Xiaowen Dong:
Transductive Kernels for Gaussian Processes on Graphs. CoRR abs/2211.15322 (2022) - [i30]Dragos Gorduza, Xiaowen Dong, Stefan Zohren:
Understanding stock market instability via graph auto-encoders. CoRR abs/2212.04974 (2022) - 2021
- [j16]Mahmoud Ramezani Mayiami, Mohammad Hajimirsadeghi, Karl Skretting, Xiaowen Dong, Rick S. Blum, H. Vincent Poor:
Bayesian Topology Learning and noise removal from network data. Discov. Internet Things 1(1) (2021) - [j15]Mahmoud Ramezani-Mayiami, Mohammad Hajimirsadeghi, Karl Skretting, Xiaowen Dong, Rick S. Blum, H. Vincent Poor:
Correction to: Bayesian Topology Learning and noise removal from network data. Discov. Internet Things 1(1) (2021) - [j14]Xingyue Pu, Siu Lun Chau, Xiaowen Dong, Dino Sejdinovic:
Kernel-Based Graph Learning From Smooth Signals: A Functional Viewpoint. IEEE Trans. Signal Inf. Process. over Networks 7: 192-207 (2021) - [c17]Henry Kenlay, Dorina Thanou, Xiaowen Dong:
On The Stability of Graph Convolutional Neural Networks Under Edge Rewiring. ICASSP 2021: 8513-8517 - [c16]Bin Xin Ru, Xingchen Wan, Xiaowen Dong, Michael A. Osborne:
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels. ICLR 2021 - [c15]Henry Kenlay, Dorina Thanou, Xiaowen Dong:
Interpretable Stability Bounds for Spectral Graph Filters. ICML 2021: 5388-5397 - [c14]Ben Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein:
Beltrami Flow and Neural Diffusion on Graphs. NeurIPS 2021: 1594-1609 - [c13]Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen:
Learning to Learn Graph Topologies. NeurIPS 2021: 4249-4262 - [c12]Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong:
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation. NeurIPS 2021: 6983-6996 - [i29]Henry Kenlay, Dorina Thanou, Xiaowen Dong:
Interpretable Stability Bounds for Spectral Graph Filters. CoRR abs/2102.09587 (2021) - [i28]Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu:
Local2Global: Scaling global representation learning on graphs via local training. CoRR abs/2107.12224 (2021) - [i27]Benjamin Paul Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein:
Beltrami Flow and Neural Diffusion on Graphs. CoRR abs/2110.09443 (2021) - [i26]Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen:
Learning to Learn Graph Topologies. CoRR abs/2110.09807 (2021) - [i25]Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong:
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. CoRR abs/2110.12752 (2021) - [i24]Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong:
Adversarial Attacks on Graph Classification via Bayesian Optimisation. CoRR abs/2111.02842 (2021) - [i23]Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features. CoRR abs/2111.12128 (2021) - [i22]Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
Understanding over-squashing and bottlenecks on graphs via curvature. CoRR abs/2111.14522 (2021) - 2020
- [j13]Xiaowen Dong, Alfredo Jose Morales, Eaman Jahani, Esteban Moro, Bruno Lepri, Burçin Bozkaya, Carlos Sarraute, Yaneer Bar-Yam, Alex Pentland:
Segregated interactions in urban and online space. EPJ Data Sci. 9(1): 20 (2020) - [j12]Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard:
Graph Signal Processing for Machine Learning: A Review and New Perspectives. IEEE Signal Process. Mag. 37(6): 117-127 (2020) - [c11]Kaige Yang, Laura Toni, Xiaowen Dong:
Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis. AISTATS 2020: 3133-3143 - [c10]Oliver Gardiner, Xiaowen Dong:
Mobility Networks for Predicting Gentrification. COMPLEX NETWORKS (2) 2020: 181-192 - [c9]Henry Kenlay, Dorina Thanou, Xiaowen Dong:
On The Stability of Polynomial Spectral Graph Filters. ICASSP 2020: 5350-5354 - [c8]Yan Leng, Xiaowen Dong, Junfeng Wu, Alex Pentland:
Learning Quadratic Games on Networks. ICML 2020: 5820-5830 - [i21]Yin-Cong Zhi, Yin Cheng Ng, Xiaowen Dong:
Gaussian Processes on Graphs via Spectral Kernel Learning. CoRR abs/2006.07361 (2020) - [i20]Bin Xin Ru, Xingchen Wan, Xiaowen Dong, Michael A. Osborne:
Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel. CoRR abs/2006.07556 (2020) - [i19]Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard:
Graph signal processing for machine learning: A review and new perspectives. CoRR abs/2007.16061 (2020) - [i18]Xingyue Pu, Siu Lun Chau, Xiaowen Dong, Dino Sejdinovic:
Kernel-based Graph Learning from Smooth Signals: A Functional Viewpoint. CoRR abs/2008.10065 (2020) - [i17]Henry Kenlay, Dorina Thanou, Xiaowen Dong:
On the Stability of Graph Convolutional Neural Networks under Edge Rewiring. CoRR abs/2010.13747 (2020) - [i16]Xingchen Wan, Jie Yang, Slavi Marinov, Jan-Peter Calliess, Stefan Zohren, Xiaowen Dong:
Sentiment Diffusion in Financial News Networks and Associated Market Movements. CoRR abs/2011.06430 (2020)
2010 – 2019
- 2019
- [j11]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy 21(6): 551 (2019) - [j10]Xiaowen Dong, Dorina Thanou, Michael G. Rabbat, Pascal Frossard:
Learning Graphs From Data: A Signal Representation Perspective. IEEE Signal Process. Mag. 36(3): 44-63 (2019) - [p1]Albert Ali Salah, Alex Pentland, Bruno Lepri, Emmanuel Letouzé, Yves-Alexandre de Montjoye, Xiaowen Dong, Özge Dagdelen, Patrick Vinck:
Introduction to the Data for Refugees Challenge on Mobility of Syrian Refugees in Turkey. Data for Refugees Challenge 2019: 3-27 - [i15]Kaige Yang, Xiaowen Dong, Laura Toni:
Error Analysis on Graph Laplacian Regularized Estimator. CoRR abs/1902.03720 (2019) - [i14]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR abs/1906.01101 (2019) - [i13]Kaige Yang, Xiaowen Dong, Laura Toni:
Laplacian-regularized graph bandits: Algorithms and theoretical analysis. CoRR abs/1907.05632 (2019) - [i12]Xiaowen Dong, Alfredo Jose Morales, Eaman Jahani, Esteban Moro, Bruno Lepri, Burçin Bozkaya, Carlos Sarraute, Yaneer Bar-Yam, Alex Pentland:
Segregated interactions in urban and online spaces. CoRR abs/1911.04027 (2019) - [i11]Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
A Maximum Entropy approach to Massive Graph Spectra. CoRR abs/1912.09068 (2019) - 2018
- [j9]Xiaowen Dong, Joachim Meyer, Erez Shmueli, Burçin Bozkaya, Alex Pentland:
Methods for quantifying effects of social unrest using credit card transaction data. EPJ Data Sci. 7(1): 8 (2018) - [j8]Erdem Kaya, Xiaowen Dong, Yoshihiko Suhara, Selim Balcisoy, Burçin Bozkaya, Alex 'Sandy' Pentland:
Behavioral attributes and financial churn prediction. EPJ Data Sci. 7(1): 41 (2018) - [j7]Xiaowen Dong, Yoshihiko Suhara, Burçin Bozkaya, Vivek K. Singh, Bruno Lepri, Alex 'Sandy' Pentland:
Social Bridges in Urban Purchase Behavior. ACM Trans. Intell. Syst. Technol. 9(3): 33:1-33:29 (2018) - [i10]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
Entropic Spectral Learning in Large Scale Networks. CoRR abs/1804.06802 (2018) - [i9]Xiaowen Dong, Dorina Thanou, Michael G. Rabbat, Pascal Frossard:
Learning Graphs from Data: A Signal Representation Perspective. CoRR abs/1806.00848 (2018) - [i8]Albert Ali Salah, Alex Pentland, Bruno Lepri, Emmanuel Letouzé, Patrick Vinck, Yves-Alexandre de Montjoye, Xiaowen Dong, Özge Dagdelen:
Data for Refugees: The D4R Challenge on Mobility of Syrian Refugees in Turkey. CoRR abs/1807.00523 (2018) - [i7]Yan Leng, Xiaowen Dong, Alex Pentland:
Learning Quadratic Games on Networks. CoRR abs/1811.08790 (2018) - 2017
- [j6]Dorina Thanou, Xiaowen Dong, Daniel Kressner, Pascal Frossard:
Learning Heat Diffusion Graphs. IEEE Trans. Signal Inf. Process. over Networks 3(3): 484-499 (2017) - 2016
- [j5]Xiaowen Dong, Dorina Thanou, Pascal Frossard, Pierre Vandergheynst:
Learning Laplacian Matrix in Smooth Graph Signal Representations. IEEE Trans. Signal Process. 64(23): 6160-6173 (2016) - [c7]Renata Khasanova, Xiaowen Dong, Pascal Frossard:
Multi-modal Image Retrieval with Random Walk on Multi-layer Graphs. ISM 2016: 1-6 - [i6]Renata Khasanova, Xiaowen Dong, Pascal Frossard:
Multi-modal image retrieval with random walk on multi-layer graphs. CoRR abs/1607.03406 (2016) - [i5]Dorina Thanou, Xiaowen Dong, Daniel Kressner, Pascal Frossard:
Learning heat diffusion graphs. CoRR abs/1611.01456 (2016) - 2015
- [j4]Xiaowen Dong, Dimitrios Mavroeidis, Francesco Calabrese, Pascal Frossard:
Multiscale event detection in social media. Data Min. Knowl. Discov. 29(5): 1374-1405 (2015) - [c6]Xiaowen Dong, Dorina Thanou, Pascal Frossard, Pierre Vandergheynst:
Laplacian matrix learning for smooth graph signal representation. ICASSP 2015: 3736-3740 - 2014
- [j3]Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov:
Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds. IEEE Trans. Signal Process. 62(4): 905-918 (2014) - [i4]Xiaowen Dong, Dimitrios Mavroeidis, Francesco Calabrese, Pascal Frossard:
Multiscale Event Detection in Social Media. CoRR abs/1404.7048 (2014) - [i3]Xiaowen Dong, Dorina Thanou, Pascal Frossard, Pierre Vandergheynst:
Learning Graphs from Signal Observations under Smoothness Prior. CoRR abs/1406.7842 (2014) - 2013
- [c5]Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov:
Clustering on multi-layer graphs via subspace analysis on Grassmann manifolds. GlobalSIP 2013: 993-996 - [c4]Xiaowen Dong, Antonio Ortega, Pascal Frossard, Pierre Vandergheynst:
Inference of mobility patterns via Spectral Graph Wavelets. ICASSP 2013: 3118-3122 - [c3]Michele Berlingerio, Francesco Calabrese, Giusy Di Lorenzo, Xiaowen Dong, Yiannis Gkoufas, Dimitrios Mavroeidis:
SaferCity: A System for Detecting and Analyzing Incidents from Social Media. ICDM Workshops 2013: 1077-1080 - [i2]Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov:
Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds. CoRR abs/1303.2221 (2013) - 2012
- [j2]Zhe Wang, Kai Hu, Ke Xu, Baolin Yin, Xiaowen Dong:
Structural analysis of network traffic matrix via relaxed principal component pursuit. Comput. Networks 56(7): 2049-2067 (2012) - [j1]Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov:
Clustering With Multi-Layer Graphs: A Spectral Perspective. IEEE Trans. Signal Process. 60(11): 5820-5831 (2012) - [c2]Xuan Zhang, Xiaowen Dong, Pascal Frossard:
Learning of structured graph dictionaries. ICASSP 2012: 3373-3376 - 2011
- [c1]Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov:
A regularization framework for mobile social network analysis. ICASSP 2011: 2140-2143 - [i1]Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov:
Clustering with Multi-Layer Graphs: A Spectral Perspective. CoRR abs/1106.2233 (2011)
Coauthor Index
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