Guide to mobile data analytics in refugee scenarios: The 'Data for Refugees Challenge' study [Link]
A. A. Salah, A. Pentland, B. Lepri, E. Letouzé, Y.-A. de Montjoye, X. Dong and P. Vinck (Eds.), Springer, 2019.
Graph learning [Link]
X. Dong, D. Thanou, M. Rabbat and P. Frossard
Graph spectral image processing, G. Cheung and E. Magli (Eds.), ISTE, 2021, pp. 31-62.
Introduction to the Data for Refugees Challenge on mobility of Syrian refugees in Turkey [Link]
A. A. Salah, A. Pentland, B. Lepri, E. Letouzé, Y.-A. de Montjoye, X. Dong, Ö. Dağdelen and P. Vinck
Guide to mobile data analytics in refugee scenarios: The 'Data for Refugees Challenge' study, A. A. Salah, A. Pentland, B. Lepri, E. Letouzé, Y.-A. de Montjoye, X. Dong and P. Vinck (Eds.), Springer, 2019, pp. 3-27.
The rippling effect of social influence via phone communication network [Link]
Y. Leng, X. Dong, E. Moro and A. Pentland
Complex spreading phenomena in social systems: Influence and contagion in real-world social networks, S. Lehmann and Y.-Y. Ahn (Eds.), Springer, 2018, pp. 323-333.
Understanding stock market instability via graph auto-encoders [PDF]
D. Gorduza, S. Zohren, and X. Dong
EPJ Data Science, vol. 14, article no. 13, February 2025.
Forecasting realized volatility with spillover effects: Perspectives from graph neural networks [PDF]
C. Zhang, X. Pu, M. Cucuringu and X. Dong
International Journal of Forecasting, vol. 41, no. 1, pp. 377-397, January-March 2025.
Large language models for financial and investment management: Models, opportunities, and challenges [PDF]
Y. Kong, Y. Nie, X. Dong, J. M. Mulvey, H. V. Poor, Q. Wen and S. Zohren
Journal of Portfolio Management, vol. 51, no. 2, pp. 211-231, December 2024.
Large language models for financial and investment management: Applications and benchmarks [PDF]
Y. Kong, Y. Nie, X. Dong, J. M. Mulvey, H. V. Poor, Q. Wen and S. Zohren
Journal of Portfolio Management, vol. 51, no. 2, pp. 162-210, December 2024.
Graph-based methods for forecasting realized covariances [PDF]
C. Zhang, X. Pu, M. Cucuringu and X. Dong
Journal of Financial Econometrics, article no. nbae026, November 2024.
Long-range social influence in phone communication networks on offline adoption decisions [PDF]
Y. Leng, X. Dong, E. Moro and A. Pentland
Information Systems Research, vol. 35, no. 1, pp. 318-338, March 2024.
Wisdom of the crowds or ignorance of the masses? A data-driven guide to WallStreetBets [PDF]
V. Semenova, D. Gorduza, W. Wildi, X. Dong and S. Zohren
Journal of Portfolio Management, vol. 50, no. 4, pp. 88-106, February 2024.
Graph similarity learning for change-point detection in dynamic networks [PDF]
D. Sulem, H. Kenlay, M. Cucuringu and X. Dong
Machine Learning, vol. 113, pp. 1-44, January 2024.
Behavioral changes during the COVID-19 pandemic decreased income diversity of urban encounters [PDF]
T. Yabe, B. G. B. Bueno, X. Dong, A. Pentland and E. Moro
Nature Communications, vol. 14, article no. 2310, April 2023.
Gaussian processes on graphs via spectral kernel learning [PDF]
Y.-C. Zhi, Y. C. Ng and X. Dong
IEEE Transactions on Signal and Information Processing over Networks, vol. 9, no. 3, pp. 304-314, April 2023.
Local2Global: A distributed approach for scaling representation learning on graphs [PDF]
L. G. S. Jeub, G. Colavizza, X. Dong, M. Bazzi and M. Cucuringu
Machine Learning, vol. 112, pp. 1663-1692, February 2023.
Maximum entropy approach to massive graph spectrum learning with applications [PDF]
D. Granziol, B. Ru, X. Dong, S. Zohren, M. A. Osborne and S. Roberts
Algorithms, Special Issue on Extreme Algorithmics: Analysis of Huge, Noisy, and Dynamic Networked Data, vol. 15, no. 6, article no. 209, June 2022.
Interaction data are identifiable even across long periods of time [PDF]
A.-M. Cretu, F. Monti, S. Marrone, X. Dong, M. M. Bronstein and Y.-A. de Montjoye
Nature Communications, vol. 13, article no. 313, January 2022.
Mobility patterns are associated with experienced income segregation in large US cities [PDF]
E. Moro, D. Calacci, X. Dong and A. Pentland
Nature Communications, vol. 12, article no. 4633, July 2021.
Bayesian topology learning and noise removal from network data [PDF]
M. R. Mayiami, M. Hajimirsadeghi, K. Skretting, X. Dong, R. S. Blum and H. V. Poor
Discover Internet of Things, vol. 1, article no. 11, March 2021.
Kernel-based graph learning from smooth signals: A functional viewpoint [PDF]
X. Pu, S. L. Chau, X. Dong and D. Sejdinovic
IEEE Transactions on Signal and Information Processing over Networks, vol. 7, pp. 192-207, February 2021.
Sentiment correlation in financial news networks and associated market movements [PDF]
X. Wan, J. Yang, S. Marinov, J.-P. Calliess, S. Zohren and X. Dong
Scientific Reports, vol. 11, article no. 3062, February 2021.
Graph signal processing for machine learning: A review and new perspectives [PDF] [Extended version]
X. Dong, D. Thanou, L. Toni, M. M. Bronstein and P. Frossard
IEEE Signal Processing Magazine, vol. 37, no. 6, pp. 117-127, November 2020.
Segregated interactions in urban and online space [PDF]
X. Dong, A. J. Morales, E. Jahani, E. Moro, B. Lepri, B. Bozkaya, C. Sarraute, Y. Bar-Yam and A. Pentland
EPJ Data Science, vol. 9, article no. 20, July 2020.
Purchase patterns, socioeconomic status, and political inclination [PDF]
X. Dong, E. Jahani, A. J. Morales, B. Bozkaya, B. Lepri and A. Pentland
World Bank Economic Review, vol. 34, issue supplement_1, pp. S9-S13, February 2020.
Segregation and polarization in urban areas [PDF]
A. J. Morales, X Dong, Y. Bar-Yam and A. Pentland
Royal Society Open Science, vol. 6, no. 10, article ID 190573, October 2019.
MEMe: An accurate maximum entropy method for efficient approximations in large-scale machine learning [PDF]
D. Granziol, B. Ru, S. Zohren, X. Dong, M. A. Osborne and S. Roberts
Entropy, Special Issue on Entropy Based Inference and Optimization in Machine Learning, vol. 21, no. 6, article no. 551, May 2019.
Learning graphs from data: A signal representation perspective [PDF] [Errata]
X. Dong, D. Thanou, M. Rabbat and P. Frossard
IEEE Signal Processing Magazine, vol. 36, no. 3, pp. 44-63, May 2019.
Behavioral attributes and financial churn prediction [PDF]
E. Kaya, X. Dong, Y. Suhara, S. Balcisoy, B. Bozkaya and A. Pentland
EPJ Data Science, vol. 7, article no. 41, October 2018.
Methods for quantifying effects of social unrest using credit card transaction data [PDF]
X. Dong, J. Meyer, E. Shmueli, B. Bozkaya and A. Pentland
EPJ Data Science, vol. 7, article no. 8, April 2018.
Social bridges in urban purchase behavior [PDF]
X. Dong, Y. Suhara, B. Bozkaya, V. K. Singh, B. Lepri and A. Pentland
ACM Transactions on Intelligent Systems and Technology, Special Issue on Urban Intelligence, vol. 9, no. 3, article no. 33, February 2018.
Learning heat diffusion graphs [PDF]
D. Thanou, X. Dong, D. Kressner and P. Frossard
IEEE Transactions on Signal and Information Processing over Networks, Special Issue on Graph Signal Processing, vol. 3, no. 3, pp. 484-499, September 2017.
Learning Laplacian matrix in smooth graph signal representations [PDF] [Code]
X. Dong, D. Thanou, P. Frossard and P. Vandergheynst
IEEE Transactions on Signal Processing, vol. 64, no. 23, pp. 6160-6173, December 2016.
Multiscale event detection in social media [PDF] [Code]
X. Dong, D. Mavroeidis, F. Calabrese and P. Frossard
Data Mining and Knowledge Discovery, Special Issue of the ECMLPKDD 2015 Journal Track, vol. 29, no. 5, pp. 1374-1405, September 2015.
Clustering on multi-layer graphs via subspace analysis on Grassmann manifolds [PDF] [Code] [TSP cover]
X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
IEEE Transactions on Signal Processing, vol. 62, no. 4, pp. 905-918, February 2014.
Clustering with multi-layer graphs: A spectral perspective [PDF] [Code]
X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
IEEE Transactions on Signal Processing, vol. 60, no. 11, pp. 5820-5831, November 2012.
Structural analysis of network traffic matrix via relaxed principal component pursuit [PDF]
Z. Wang, K. Hu, K. Xu, B. Yin and X. Dong
Computer Networks, vol. 56, no. 7, pp. 2049-2067, May 2012.
Heterogeneous graph structure learning through the lens of data-generating processes [PDF]
K. Jiang, B. Tang, X. Dong and L. Toni
International Conference on Artificial Intelligence and Statistics (AISTATS), May 2025.
Separation power of equivariant neural networks [PDF]
M. Pacini, X. Dong, B. Lepri and G. Santin
International Conference on Learning Representations (ICLR), April 2025.
Neural spacetimes for DAG representation learning [PDF]
H. Sáez de Ocáriz Borde, A. Kratsios, M. T. Law, X. Dong and M. M. Bronstein
International Conference on Learning Representations (ICLR), April 2025.
Bundle neural networks for message diffusion on graphs [PDF]
J. Bamberger, F. Barbero, X. Dong and M. M. Bronstein
International Conference on Learning Representations (ICLR), April 2025.
Training-free message passing for learning on hypergraphs [PDF]
B. Tang, Z. Liu, K. Jiang, S. Chen and X. Dong
International Conference on Learning Representations (ICLR), April 2025.
Rough transformers: Lightweight and continuous time series modelling through signature patching [PDF]
F. Moreno-Pino, Á. Arroyo, H. Waldon, X. Dong and Á. Cartea
Conference on Neural Information Processing Systems (NeurIPS), December 2024.
Bayesian optimization of functions over node subsets in graphs [PDF]
H. Liang, X. Wan and X. Dong
Conference on Neural Information Processing Systems (NeurIPS), December 2024.
Extracting alpha from financial analyst networks [PDF]
D. Gorduza, Y. Kong, X. Dong and S. Zohren
ACM International Conference on AI in Finance (ICAIF), November 2024.
STEntConv: Predicting disagreement between Reddit users with stance detection and a signed graph convolutional network [PDF]
I. Lorge, L. Zhang, X. Dong and J. Pierrehumbert
Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), May 2024.
A characterization theorem for equivariant networks with point-wise activations [PDF]
M. Pacini, X. Dong, B. Lepri and G. Santin
International Conference on Learning Representations (ICLR), May 2024.
Hypergraph transformer for semi-supervised classification [PDF]
Z. Liu, B. Tang, Z. Ye, X. Dong, S. Chen and Y. Wang
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), April 2024.
Hypergraph-MLP: Learning on hypergraphs without message passing [PDF]
B. Tang, S. Chen and X. Dong
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), April 2024.
Neural latent geometry search: Product manifold inference via Gromov-Hausdorff-informed Bayesian optimization [PDF]
H. Sáez de Ocáriz Borde, Á. Arroyo, I. Morales, I. Posner and X. Dong
Conference on Neural Information Processing Systems (NeurIPS), December 2023.
Bayesian optimisation of functions on graphs [PDF]
X. Wan, P. Osselin, H. Kenlay, B. Ru, M. A. Osborne and X. Dong
Conference on Neural Information Processing Systems (NeurIPS), December 2023.
Graph classification Gaussian processes via spectral features [PDF]
F. L. Opolka, Y.-C. Zhi, P. Liò and X. Dong
Conference on Uncertainty in Artificial Intelligence (UAI), July-August 2023.
Structure-aware robustness certificates for graph classification [PDF]
P. Osselin, H. Kenlay and X. Dong
Conference on Uncertainty in Artificial Intelligence (UAI), July-August 2023.
DRew: Dynamically rewired message passing with delay [PDF] [Blog]
B. Gutteridge, X. Dong, M. M. Bronstein and F. Di Giovanni
International Conference on Machine Learning (ICML), July 2023.
On the impact of sample size in reconstructing graph signals [PDF]
B. Sripathmanathan, X. Dong and M. M. Bronstein
International conference on Sampling Theory and Applications (SampTA), July 2023.
Learning hypergraphs from signals with dual smoothness prior [PDF]
B. Tang, S. Chen and X. Dong
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), June 2023.
On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features [PDF] [Blog]
E. Rossi, H. Kenlay, M. I. Gorinova, B. P. Chamberlain, X. Dong and M. M. Bronstein
Learning on Graphs Conference (LoG), December 2022.
Learning to infer structures of network games [PDF] [Blog]
E. Rossi, F. Monti, Y. Leng, M. M. Bronstein and X. Dong
International Conference on Machine Learning (ICML), July 2022.
Modeling ideological salience and framing in polarized online groups with graph neural networks and structured sparsity [PDF]
V. Hofmann, X. Dong, J. B. Pierrehumbert and H. Schuetze
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL Findings), July 2022.
Understanding over-squashing and bottlenecks on graphs via curvature [PDF] [Blog]
J. Topping, F. Di Giovanni, B. P. Chamberlain, X. Dong and M. M. Bronstein
International Conference on Learning Representations (ICLR), April 2022.
Adaptive Gaussian processes on graphs via spectral graph wavelets [PDF]
F. L. Opolka, Y.-C. Zhi, P. Liò and X. Dong
International Conference on Artificial Intelligence and Statistics (AISTATS), March 2022.
Beltrami flow and neural diffusion on graphs [PDF]
B. P. Chamberlain, J. Rowbottom, D. Eynard, F. Di Giovanni, X. Dong and M. M. Bronstein
Conference on Neural Information Processing Systems (NeurIPS), December 2021.
Learning to learn graph topologies [PDF]
X. Pu, T. Cao, X. Zhang, X. Dong and S. Chen
Conference on Neural Information Processing Systems (NeurIPS), December 2021.
Adversarial attacks on graph classifiers via Bayesian optimisation [PDF]
X. Wan, H. Kenlay, B. Ru, A. Blaas, M. A. Osborne and X. Dong
Conference on Neural Information Processing Systems (NeurIPS), December 2021.
Interpretable stability bounds for spectral graph filters [PDF]
H. Kenlay, D. Thanou and X. Dong
International Conference on Machine Learning (ICML), July 2021.
On the stability of graph convolutional neural networks under edge rewiring [PDF]
H. Kenlay, D. Thanou and X. Dong
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), June 2021.
Interpretable neural architecture search via Bayesian optimisation with Weisfeiler-Lehman kernels [PDF]
B. Ru, X Wan, X. Dong and M. A. Osborne
International Conference on Learning Representations (ICLR), May 2021.
Mobility networks for predicting gentrification [PDF]
O. Gardiner and X. Dong
International Conference on Complex Networks and their Applications (Complex Networks), December 2020.
Laplacian-regularized graph bandits: Algorithms and theoretical analysis [PDF]
K. Yang, X. Dong and L. Toni
International Conference on Artificial Intelligence and Statistics (AISTATS), August 2020.
Learning quadratic games on networks [PDF]
Y. Leng, X. Dong, J. Wu and A. Pentland
International Conference on Machine Learning (ICML), July 2020.
On the stability of polynomial spectral graph filters [PDF]
H. Kenlay, D. Thanou and X. Dong
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2020.
Multi-modal image retrieval with random walk on multi-layer graphs [PDF]
R. Khasanova, X. Dong and P. Frossard
IEEE International Symposium on Multimedia (ISM), San Jose, CA, USA, December 2016.
Laplacian matrix learning for smooth graph signal representation [PDF]
X. Dong, D. Thanou, P. Frossard and P. Vandergheynst
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, April 2015.
SaferCity: A system for detecting incidents from social media [PDF]
M. Berlingerio, F. Calabrese, G. Di Lorenzo, X. Dong, Y. Gkoufas and D. Mavroeidis
IEEE International Conference on Data Mining Workshops (ICDMW), Dallas, TX, USA, December 2013.
Clustering on multi-layer graphs via subspace analysis on Grassmann manifolds [PDF]
X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
IEEE Global Conference on Signal and Information Processing (GlobalSIP), Austin, TX, USA, December 2013.
Inference of mobility patterns via spectral graph wavelets [PDF]
X. Dong, A. Ortega, P. Frossard and P. Vandergheynst
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May 2013.
Learning of structured graph dictionaries [PDF]
X. Zhang, X. Dong and P. Frossard
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, March 2012.
A regularization framework for mobile social network analysis [PDF]
X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Prague, Czech Republic, May 2011.
Graph classification Gaussian processes via Hodgelet spectral features
M. Alain, S. Takao, B. Rieck, X. Dong and E. Noutahi
NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty, December 2024.
Hypergraph transformer for semi-supervised classification
Z. Liu, B. Tang, Z. Ye, X. Dong, S. Chen and Y. Wang
Graph Signal Analysis & Learning Workshop (GSAL), July 2024.
Bundle neural networks for message diffusion on graphs
J. Bamberger, F. Barbero, X. Dong and M. M. Bronstein
ICML 2024 Workshop on Geometry-grounded Representation Learning and Generative Modeling, July 2024.
Heterogeneous graph structure learning: A statistical perspective
K. Jiang, B. Tang, X. Dong and L. Toni
Graph Signal Processing Workshop (GSP), June 2024.
On the impact of sample size in reconstructing signals with graph Laplacian regularisation
B. Sripathmanathan, X. Dong and M. M. Bronstein
Graph Signal Processing Workshop (GSP), June 2024.
Decentralized and lifelong-adaptive multi-agent collaborative learning
S. Tang, R. Ye, C. Xu, X. Dong, S. Chen and Y. Wang
Graph Signal Processing Workshop (GSP), June 2024.
Hypergraph transformer for semi-supervised classification
Z. Liu, B. Tang, Z. Ye, X. Dong, S. Chen and Y. Wang
Graph Signal Processing Workshop (GSP), June 2024.
A novel smoothness prior for hypergraph machine learning
B. Tang, S. Chen and X. Dong
Graph Signal Processing Workshop (GSP), June 2024.
On the stability of graph spectral filters: A probabilistic perspective
N. Zhang, H. Kenlay, M. Cucuringu and X. Dong
Graph Signal Processing Workshop (GSP), June 2024.
Rough transformers for continuous and efficient time-series modelling
F. Moreno-Pino, Á. Arroyo, H. Waldon, X. Dong and Á. Cartea
ICLR 2024 Workshop on Learning from Time Series for Health, May 2024.
Maximum likelihood estimation on stochastic blockmodels for directed graph clustering
M. Cucuringu, X. Dong and N. Zhang
International Conference on Complex Networks and Their Applications (Complex Networks), November 2023.
Point-wise activations and steerable convolutional networks
M. Pacini, X. Dong, B. Lepri and G. Santin
Learning on Graphs Conference (LoG), November 2023.
Learning to learn network momentum
X. Pu, S. Roberts, X. Dong and S. Zohren
ICAIF 2023 Workshop on NLP and Network Analysis in Financial Applications, November 2023.
Behavioral changes during the COVID-19 pandemic decreased income diversity of urban encounters
T. Yabe, B. G. B. Bueno, X. Dong, A. Pentland and E. Moro
NetMob, October 2023.
Gromov-Hausdorff distances for comparing product manifolds of model spaces
H. Sáez de Ocáriz Borde, Á. Arroyo, I. Morales, I. Posner and X. Dong
ICML 2023 Workshop on Topology, Algebra, and Geometry in Machine Learning, July 2023.
Predicting polarisation of dynamic social networks via graph auto-encoders
L. Zhang, I. Lorge, J. B. Pierrehumbert and X. Dong
International Conference on Computational Social Science (IC2S2), July 2023.
Learning heterogeneous graphs with generalized smoothness
K. Jiang, L. Toni and X. Dong
Graph Signal Processing Workshop (GSP), June 2023.
On the impact of sample size in reconstructing graph signals
B. Sripathmanathan, X. Dong and M. M. Bronstein
Graph Signal Processing Workshop (GSP), June 2023.
Unrolled graph learning for multi-agent collaboration
E. Zhang, S. Tang, X. Dong, S. Chen and Y. Wang
Graph Signal Processing Workshop (GSP), June 2023.
Learning hypergraphs from signals with dual smoothness prior
B. Tang, S. Chen and X. Dong
Graph Signal Processing Workshop (GSP), June 2023.
Graph classification Gaussian processes via spectral features
F. L. Opolka, Y.-C. Zhi, P. Liò and X. Dong
Graph Signal Processing Workshop (GSP), June 2023.
Transductive kernels for Gaussian processes on graphs
Y.-C. Zhi, F. L. Opolka, Y. C. Ng, P. Liò and X. Dong
Graph Signal Processing Workshop (GSP), June 2023.
On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features
E. Rossi, H. Kenlay, M. I. Gorinova, B. P. Chamberlain, X. Dong and M. M. Bronstein
NeurIPS 2022 Workshop on New Frontiers in Graph Learning, December 2022.
Understanding stock market instability via graph auto-encoders
D. Gorduza, X. Dong and S. Zohren
NeurIPS 2022 Workshop on Graph Learning for Industrial Applications, December 2022.
Can social connections be protected when behavioral data is public?
Y. Leng, Y. Chen, X. Dong, J. Wu and G. Shi
Workshop on Information Technology and Systems (WITS), December 2022.
Structure-aware robustness certificates for graph classification
P. Osselin, H. Kenlay and X. Dong
International Workshop on Mining and Learning with Graphs (MLG), September 2022.
On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features
E. Rossi, H. Kenlay, M. I. Gorinova, B. P. Chamberlain, X. Dong and M. M. Bronstein
ECML PKDD 2022 Workshop on Graph Quality, September 2022.
Graph similarity learning for change-point detection in dynamic networks
D. Sulem, H. Kenlay, M. Cucuringu and X. Dong
NetSci 2022 Satellite Symposium on Higher-Order Topology & Dynamics in Complex Networks, July 2022.
Graph similarity learning for change-point detection in dynamic networks
D. Sulem, H. Kenlay, M. Cucuringu and X. Dong
International School and Conference on Network Science (NetSci), July 2022.
Long-term behavioral changes during COVID-19 have increased urban segregation
T. Yabe, B. G. B. Bueno, X. Dong, A. Pentland and E. Moro
International School and Conference on Network Science (NetSci), July 2022.
Long-term impacts of COVID-19 on urban income segregation
T. Yabe, B. G. B. Bueno, X. Dong, A. Pentland and E. Moro
International Conference on Computational Social Science (IC2S2), July 2022.
Interaction data are identifiable even across long periods of time
A.-M. Cretu, F. Monti, S. Marrone, X. Dong, M. M. Bronstein and Y.-A. de Montjoye
NeurIPS 2021 Workshop on Privacy in Machine Learning, December 2021.
Interaction data are identifiable even across long periods of time
A.-M. Cretu, F. Monti, S. Marrone, X. Dong, M. M. Bronstein and Y.-A. de Montjoye
ACM CCS 2021 Workshop on Privacy Preserving Machine Learning, November 2021.
Local2Global: Scaling global representation learning on graphs via local training
L. G. S. Jeub, G. Colavizza, X. Dong, M. Bazzi and M. Cucuringu
KDD 2021 Workshop on Deep Learning on Graphs: Methods and Applications, August 2021.
Attacking graph classification via Bayesian optimisation
X. Wan, H. Kenlay, B. Ru, A. Blaas, M. A. Osborne and X. Dong
ICML 2021 Workshop on Adversarial Machine Learning, July 2021.
On the stability of graph convolutional neural networks under edge rewiring
H. Kenlay, D. Thanou and X. Dong
ICLR 2021 Workshop on Geometrical and Topological Representation Learning, May 2021.
On the stability of graph convolutional neural networks under edge rewiring
H. Kenlay, D. Thanou and X. Dong
AAAI 2021 Workshop on Deep Learning on Graphs, February 2021.
Gaussian processes on graphs via spectral kernel learning
Y.-C. Zhi, Y. C. Ng and X. Dong
AAAI 2021 Workshop on Graphs and more Complex Structures for Learning and Reasoning, February 2021.
Geometric deep learning for music genre classification
M. Sathyamurthy, X. Dong and M. Pawan Kumar
International Workshop on Machine Learning and Music (MML), September 2020.
Segregated behaviors in American cities
E. Moro, D. Calacci, X. Dong and A. Pentland
International Conference on Computational Social Science (IC2S2), July 2020.
Beyond exposure: The complex pattern of social influence
Y. Leng, X. Dong, M. Travizano, E. Moro and A. Pentland
International Conference on Computational Social Science (IC2S2), July 2020.
Entropic graph spectrum
D. Granziol, B. Ru, S. Zohren, X. Dong, M. A. Osborne and S. Roberts
NeurIPS 2019 Workshop on Information Theory and Machine Learning, Vancouver, Canada, December 2019.
Mapping segregation in urban areas
A. J. Morales, X. Dong, Y. Bar-Yam and A. Pentland
International Conference on Computational Social Science (IC2S2), Amsterdam, Netherlands, July 2019.
Learning network structure in linear quadratic games
Y. Leng, X. Dong and A. Pentland
International Conference on Computational Social Science (IC2S2), Amsterdam, Netherlands, July 2019.
Economical segregation of encounter networks in cities
E. Moro, D. Calacci, X. Dong and A. Pentland
NetMob, Oxford, UK, July 2019.
Mapping segregation in urban areas
A. J. Morales, X. Dong, Y. Bar-Yam and A. Pentland
International School and Conference on Network Science (NetSci), Burlington, VT, USA, May 2019.
Beyond exposure: The complex pattern of social influence
Y. Leng, X. Dong, E. Moro and A. Pentland
International School and Conference on Network Science (NetSci), Burlington, VT, USA, May 2019.
Learning quadratic games on networks
Y. Leng, X. Dong and A. Pentland
International Conference on Complex Networks and Their Applications (Complex Networks), Cambridge, UK, December 2018.
Inferring mobile app preference via multi-view geometric information fusion
Y. Leng, X. Dong, D. Adjodah and A. Pentland
Conference on Information Systems and Technology (CIST), Phoenix, AZ, USA, November 2018.
Quantifying heterogeneous social influence via ego network structures
Y. Leng, X. Dong, E. Moro and A. Pentland
Conference on Digital Experimentation (CODE), Cambridge, MA, USA, October 2018.
Mapping segregation in urban areas
A. J. Morales, Y. Bar-Yam, X. Dong and A. Pentland
Conference on Complex Systems (CCS), Thessaloniki, Greece, September 2018.
Economical segregation of encounter networks in cities
E. Moro, D. Calacci, X. Dong, M. Cebrian and A. Pentland
International Conference on Computational Social Science (IC2S2), Evanston, IL, USA, July 2018.
Economical segregation of encounter networks in cities
E. Moro, D. Calacci, X. Dong, M. Cebrian and A. Pentland
International School and Conference on Network Science (NetSci), Paris, France, June 2018.
A Bayesian learning model for decision-making in social networks
Y. Leng, X. Dong, E. Moro and A. Pentland
International School and Conference on Network Science (NetSci), Paris, France, June 2018.
Inferring mobile app preference via multi-view geometric information fusion
Y. Leng, X. Dong, D. Adjodah and A. Pentland
Graph Signal Processing Workshop (GSP), Lausanne, Switzerland, June 2018.
A large-scale experiment and model of social influence in phone communication networks
Y. Leng, X. Dong, E. Moro and A. Pentland
Annual Conference on Network Science and Economics (NetSciEcon), Nashville, TN, USA, April 2018.
Coupling patterns of virtual and physical behavior
A. J. Morales, X. Dong, Y. Bar-Yam and A. Pentland
Conference on Complex Systems (CCS), Cancún, Mexico, September 2017.
Coupling patterns of virtual and physical behavior
A. J. Morales, X. Dong, Y. Bar-Yam, B. Bozkaya and A. Pentland
International Conference on Computational Social Science (IC2S2), Cologne, Germany, July 2017.
The ripple effect: You are more influential than you think
Y. Leng, X. Dong, E. Moro and A. Pentland
International School and Conference on Network Science (NetSci), Indianapolis, IN, USA, June 2017.
The ripple effect of social influence in phone communication network
Y. Leng, X. Dong, E. Moro and A. Pentland
NetMob, Milan, Italy, April 2017.
Spatial structure of cities: How neighborhoods' activity patterns shape inequality and polycentricity
M. De Nadai, X. Dong, R. Larcher, A. Pentland and B. Lepri
International Conference on Computational Social Science (IC2S2), Evanston, IL, USA, June 2016.
DeepShop: Understanding purchase patterns via deep learning
Y. Suhara, X. Dong, B. Bozkaya and A. Pentland
International Conference on Computational Social Science (IC2S2), Evanston, IL, USA, June 2016.
Purchase patterns, socioeconomic status, and political inclination
X. Dong, E. Jahani, A. J. Morales, B. Bozkaya, B. Lepri and A. Pentland
International Conference on Computational Social Science (IC2S2), Evanston, IL, USA, June 2016.
Learning graph Laplacians: A signal representation perspective
D. Thanou, X. Dong and P. Frossard
Graph Signal Processing Workshop (GSP), Philadelphia, PA, USA, May 2016.
Social bridges in community purchase behavior
X. Dong, Y. Suhara, B. Bozkaya, V. K. Singh and A. Pentland
Workshop on Information in Networks (WIN), New York, NY, USA, October 2015.
Methods for clustering multi-layer graphs in mobile networks
X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
Interdisciplinary Workshop on Information and Decision in Social Networks (WIDS), Cambridge, MA, USA, May-June 2011.
System for identifying, monitoring and ranking incidents from social media [Link]
M. Berlingerio, X. Dong, A. Gkoulalas-Divanis and D. Mavroeidis
US Patent: US9397904 B2, July 2016.