Fragkiskos D. Malliaros

发表

Core Decomposition of Uncertain Graphs Using Representative Instances

Michalis Vazirgiannis, Apostolos N. Papadopoulos, Damien Seux, 2017 .

The core decomposition of networks: theory, algorithms and applications

Michalis Vazirgiannis, Christos Giatsidis, Apostolos N. Papadopoulos, 2019, The VLDB Journal.

Fast Robustness Estimation in Large Social Graphs: Communities and Anomaly Detection

Christos Faloutsos, Vasileios Megalooikonomou, Fragkiskos D. Malliaros, 2012, SDM.

A k-core Decomposition Framework for Graph Clustering pdf

Dimitrios M. Thilikos, Michalis Vazirgiannis, Christos Giatsidis, 2016, ArXiv.

NodeSig: Random Walk Diffusion meets Hashing for Scalable Graph Embeddings pdf

Apostolos N. Papadopoulos, Fragkiskos D. Malliaros, Abdulkadir Çelikkanat, 2020, ArXiv.

SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Konstantinos Skianis, 2016, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW).

Expansion Properties of Large Social Graphs

Vasileios Megalooikonomou, Fragkiskos D. Malliaros, V. Megalooikonomou, 2011, DASFAA Workshops.

Semi-Supervised Learning and Graph Neural Networks for Fake News Detection

Fragkiskos D. Malliaros, Adrien Benamira, Benjamin Devillers, 2019, 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

Graph-based term weighting for text categorization

Fragkiskos D. Malliaros, Konstantinos Skianis, Konstantinos Skianis, 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

Dynamic monitoring of software use with recurrent neural networks

Fragkiskos D. Malliaros, Paul-Henry Cournède, Chloé Adam, 2020, Data Knowl. Eng..

BigNet 2018 Chairs' Welcome & Organization

Achim Rettinger, Yuxiao Dong, Jie Tang, 2018, WWW.

Estimating robustness in large social graphs

Christos Faloutsos, Vasileios Megalooikonomou, Fragkiskos D. Malliaros, 2014, Knowledge and Information Systems.

Locating influential nodes in complex networks

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Maria-Evgenia G. Rossi, 2016, Scientific Reports.

Sensitivity of Community Structure to Network Uncertainty

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Marc Mitri, 2017, SDM.

TNE: A Latent Model for Representation Learning on Networks pdf

Fragkiskos D. Malliaros, Abdulkadir Çelikkanat, Abdulkadir Çelikkanat, 2018, NIPS 2018.

BiasedWalk: Biased Sampling for Representation Learning on Graphs

Fragkiskos D. Malliaros, Duong Nguyen, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Perturb and Combine to Identify Influential Spreaders in Real-World Networks

Michalis Vazirgiannis, Jesse Read, Fragkiskos D. Malliaros, 2018, 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

To stay or not to stay: modeling engagement dynamics in social graphs

Michalis Vazirgiannis, Fragkiskos D. Malliaros, M. Vazirgiannis, 2013, CIKM.

Influence Maximization via Representation Learning pdf

Michalis Vazirgiannis, Fragkiskos D. Malliaros, George Panagopoulos, 2019, ArXiv.

Clustering and Community Detection in Directed Networks: A Survey pdf

Michalis Vazirgiannis, Fragkiskos D. Malliaros, M. Vazirgiannis, 2013, ArXiv.

Vulnerability assessment in social networks under cascade-based node departures

Michalis Vazirgiannis, Fragkiskos D. Malliaros, M. Vazirgiannis, 2015 .

Kernel Node Embeddings

Fragkiskos D. Malliaros, Abdulkadir Çelikkanat, 2019, 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

Multi-task Learning for Influence Estimation and Maximization.

Michalis Vazirgiannis, Fragkiskos D. Malliaros, George Panagopoulos, 2020 .

Advanced graph mining for community evaluation in social networks and the web

Michalis Vazirgiannis, Christos Giatsidis, Fragkiskos D. Malliaros, 2013, WSDM.

Spread it Good, Spread it Fast: Identification of Influential Nodes in Social Networks

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Maria-Evgenia G. Rossi, 2015, WWW.

Exponential Family Graph Embeddings

Fragkiskos D. Malliaros, Abdulkadir Çelikkanat, Abdulkadir Çelikkanat, 2019, AAAI.

Core Decomposition in Graphs: Concepts, Algorithms and Applications

Michalis Vazirgiannis, Apostolos N. Papadopoulos, Fragkiskos D. Malliaros, 2016, EDBT.

k-Degree anonymity on directed networks

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Jordi Casas-Roma, 2018, Knowledge and Information Systems.

A Graph Degeneracy-based Approach to Keyword Extraction

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Antoine J.-P. Tixier, 2016, EMNLP.

MATI: An efficient algorithm for influence maximization in social networks

Michalis Vazirgiannis, Christos Giatsidis, Fragkiskos D. Malliaros, 2017, PloS one.

Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text Classification

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Konstantinos Skianis, 2018, TextGraphs@NAACL-HLT.

Graph-based Text Representations: Boosting Text Mining, NLP and Information Retrieval with Graphs

Fragkiskos D. Malliaros, Michalis Vazirgiannis, M. Vazirgiannis, 2017, EMNLP 2017.

Boosting Tricks for Word Mover's Distance

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Konstantinos Skianis, 2020, ICANN.

Mining Social and Information Networks: Dynamics and Applications. (Fouille de Données dans les Réseaux Sociaux et d'Information : Dynamiques et Applications )

Fragkiskos D. Malliaros, Fragkiskos D. Malliaros, 2015 .

DiffuGreedy: An Influence Maximization Algorithm Based on Diffusion Cascades

Michalis Vazirgiannis, Fragkiskos D. Malliaros, George Panagopoulos, 2018, COMPLEX NETWORKS.

${\rm N{\small ode}S{\small ig}}$: Random Walk Diffusion meets Hashing for Scalable Graph Embeddings

Apostolos N. Papadopoulos, Fragkiskos D. Malliaros, Abdulkadir cCelikkanat, 2020 .

GraphRep: Boosting Text Mining, NLP and Information Retrieval with Graphs

Michalis Vazirgiannis, Giannis Nikolentzos, Fragkiskos D. Malliaros, 2018, CIKM.

Multiresolution similarity search in time series data: an application to EEG signals

Evangelia I. Zacharaki, Vasileios Megalooikonomou, Fragkiskos D. Malliaros, 2013, PETRA '13.

Learning Node Embeddings with Exponential Family Distributions

Fragkiskos D. Malliaros, Abdulkadir Çelikkanat, 2019, NeurIPS 2019.

Influence Maximization Using Influence and Susceptibility Embeddings

Michalis Vazirgiannis, Fragkiskos D. Malliaros, George Panagopoulos, 2020, ICWSM.

CoreCluster: A Degeneracy Based Graph Clustering Framework

Dimitrios M. Thilikos, Michalis Vazirgiannis, Christos Giatsidis, 2014, AAAI.

An Adversarial Attacker for Neural Networks in Regression Problems

Jean-Christophe Pesquet, Béatrice Pesquet-Popescu, Fragkiskos D. Malliaros, 2021, AISafety@IJCAI.

Learning Graph Representations for Influence Maximization

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis, 2021 .

Learning to Maximize Influence pdf

Michalis Vazirgiannis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis, 2021, ArXiv.

Multiple Kernel Representation Learning on Networks pdf

Fragkiskos D. Malliaros, Yanning Shen, Abdulkadir Celikkanat, 2021, ArXiv.

Topic-aware latent models for representation learning on networks pdf

Fragkiskos D. Malliaros, Abdulkadir Çelikkanat, Abdulkadir Çelikkanat, 2021, Pattern Recognit. Lett..

Grigorios Tsoumakas, Apostolos N. Papadopoulos, Fragkiskos D. Malliaros, 2022, ArXiv.

Multiomics Data Integration for Gene Regulatory Network Inference with Exponential Family Embeddings

Fragkiskos D. Malliaros, Laurent Duval, Abdulkadir Çelikkanat, 2021, 2021 29th European Signal Processing Conference (EUSIPCO).

GraphSVX: Shapley Value Explanations for Graph Neural Networks

Fragkiskos D. Malliaros, Alexandre Duval, Alexandre Duval, 2021, ECML/PKDD.

Influence Learning and Maximization

Fragkiskos D. Malliaros, George Panagopoulos, 2021, ICWE.

GraphRep

Fragkiskos D. Malliaros, Michalis Vazirgiannis, Giannis Nikolentzos, 2018, Proceedings of the 27th ACM International Conference on Information and Knowledge Management.

DSS 2018 Foreword

Evangelos Pournaras, Josef Spillner, Pradeep Ravikumar, 2018, 2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems (FAS*W).

Multiple Kernel Representation Learning on Networks

Fragkiskos D. Malliaros, Yanning Shen, Abdulkadir Çelikkanat, 2021, IEEE Transactions on Knowledge and Data Engineering.

Higher-order Clustering and Pooling for Graph Neural Networks

Fragkiskos D. Malliaros, Alexandre Duval, Alexandre Duval, 2022, CIKM.

Fragkiskos D. Malliaros, Grigorios Tsoumakas, B. Liu, 2022, Briefings Bioinform..

NodeSig: Binary Node Embeddings via Random Walk Diffusion

Fragkiskos D. Malliaros, A. Papadopoulos, Abdulkadir Çelikkanat, 2020, 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks

Jhony H. Giraldo, Fragkiskos D. Malliaros, T. Bouwmans, 2022, 2212.02374.

BRANEnet: embedding multilayer networks for omics data integration

Fragkiskos D. Malliaros, L. Duval, F. Bidard, 2022, BMC Bioinformatics.

GraphSVX: Shapley Value Explanations for Graph Neural Networks

Fragkiskos D. Malliaros, Alexandre Duval, Alexandre Duval, 2021, ECML/PKDD.

Identification of Influential Nodes in Social Networks

Fragkiskos D. Malliaros, Maria-Evgenia G. Rossi, M. Vazirgiannis, 2015 .

Multi-Task Learning for Influence Estimation and Maximization

Fragkiskos D. Malliaros, M. Vazirgiannis, G. Panagopoulos, 2020, IEEE Transactions on Knowledge and Data Engineering.

Disengagement Social Contagion: Assessing Network Vulnerability under Node Departures

Fragkiskos D. Malliaros, M. Vazirgiannis, 2014 .

Maximizing Influence with Graph Neural Networks

Fragkiskos D. Malliaros, Nikolaos Tziortziotis, M. Vazirgiannis, 2021, 2108.04623.

BraneMF: integration of biological networks for functional analysis of proteins

Fragkiskos D. Malliaros, L. Duval, F. Bidard, 2022, Bioinform..

Under Consideration for Publication in Knowledge and Information Systems Estimating Robustness in Large Social Graphs

Fragkiskos D. Malliaros, C. Faloutsos, V. Megalooikonomou, 2022 .

Higher-order Sparse Convolutions in Graph Neural Networks

Jhony H. Giraldo, Fragkiskos D. Malliaros, T. Bouwmans, 2023, ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Estimating robustness in large social graphs

Fragkiskos D. Malliaros, V. Megalooikonomou, Christos Faloutsos, 2014, Knowledge and Information Systems.

On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks

Jhony H. Giraldo, Fragkiskos D. Malliaros, T. Bouwmans, 2022, CIKM.

FAENet: Frame Averaging Equivariant GNN for Materials Modeling

Fragkiskos D. Malliaros, D. Rolnick, Y. Bengio, 2023, ICML.

Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach

Fragkiskos D. Malliaros, T. D. Noia, Daniele Malitesta, 2024, ArXiv.

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems

Fragkiskos D. Malliaros, Chaitanya K. Joshi, Y. Bengio, 2023, ArXiv.

Continuous Product Graph Neural Networks

Jhony H. Giraldo, Fragkiskos D. Malliaros, Aref Einizade, 2024, ArXiv.