Silviu Maniu

Conference and Journal Papers

  1. Colin, J., & Maniu, S. (2026). Maximizing Diverse Information Exposure in Content-Based Social Networks. Transactions on Large-Scale Data- and Knowledge-Centered Systems LIX (TLDKS).
  2. Sen, A., Maniu, S., & Senellart, P. (2026). ProvSQL: A General System for Keeping Track of the Provenance and Probability of Data. IEEE International Conference on Data Engineering (ICDE). [paper]
  3. Izri, L., Groz, B., & Maniu, S. (2025). Implementing Efficient Linear Bandits via Sketches and Random Projections. IEEE International Conference on Big Data (BigData). [paper]
  4. Méloux, M., Maniu, S., Portet, F., & Peyrard, M. (2025). Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable? International Conference of Learning Representations (ICLR). [paper]
  5. Colin, J., & Maniu, S. (2024). Optimizing Diverse Information Exposure in Social Graphs. IEEE International Conference on Big Data (BigData). [paper]
  6. Iacob, A., Cautis, B., & Maniu, S. (2023). Sequential Learning Algorithms for Contextual Model-Free Influence Maximization. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). [paper]
  7. Sun, Y., Cautis, B., & Maniu, S. (2023). Social Influence-Maximizing Group Recommendation. International AAAI Conference on Web and Social Media (ICWSM). [paper]
  8. Iacob, A., Cautis, B., & Maniu, S. (2022). Contextual Bandits for Advertising Campaigns: A Diffusion-Model Independent Approach. SIAM International Conference on Data Mining (SDM). [paper]
  9. Han, X., Cheng, R., Grubenmann, T., Maniu, S., Ma, C., & Li, X. (2022). Leveraging Contextual Graphs for Stochastic Weight Completion in Sparse Road Networks. SIAM International Conference on Data Mining (SDM).
  10. Ramusat, Y., Maniu, S., & Senellart, P. (2021). Provenance-Based Algorithms for Rich Queries over Graph Databases. International Conference on Extending Database Technology (EDBT). [paper]
  11. Maniu, S., Ioannidis, S., & Cautis, B. (2020). Bandits Under The Influence. IEEE International Conference on Data Mining (ICDM). [paper] [slides]
  12. Bahri, M., Gomes, H. M., Bifet, A., & Maniu, S. (2020). Compressed Adaptive Random Forests for Evolving Data Streams. International Joint Conference on Neural Networks (IJCNN). [paper]
  13. Bahri, M., Bifet, A., Maniu, S., de Mello, R. F., & Tziortziotis, N. (2020). Compressed k-Nearest Neighbors Ensembles for Evolving Data Streams. European Conference on Artificial Intelligence (ECAI). [paper]
  14. Bahri, M., Pfahringer, B., Bifet, A., & Maniu, S. (2020). Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams. Symposium on Intelligent Data Analysis (IDA). [paper]
  15. Maniu, S., Senellart, P., & Jog, S. (2019). An Experimental Study of the Treewidth of Real-World Graph Data. International Conference of Database Theory (ICDT). [paper] [slides] [code]
  16. Lagrée, P., Cappé, O., Cautis, B., & Maniu, S. (2019). Algorithms for Online Influencer Marketing. ACM Transactions on Knowledge Discovery from Data (TKDD), 13(1). [paper] [code]
  17. Groz, B., & Maniu, S. (2019). Hypervolume Subset Selection with Small Subsets. Evolutionary Computation, 27(4).
  18. Li, X., Cheng, R., Fang, Y., Hu, J., & Maniu, S. (2018). Scalable Evaluation of k-NN Queries on Large Uncertain Graphs. International Conference on Extending Database Technology (EDBT). [paper]
  19. Bahri, M., Maniu, S., & Bifet, A. (2018). A Sketch-Based Naive Bayes Algorithm for Evolving Data Streams. IEEE International Conference on Big Data (BigData). [paper]
  20. Maniu, S., Cheng, R., & Senellart, P. (2017). An Indexing Framework for Queries on Probabilistic Graphs. ACM Transactions on Database Systems (TODS), 42(2). [paper]
  21. Lagrée, P., Cappé, O., Cautis, B., & Maniu, S. (2017). Effective Large-Scale Online Influence Maximization. IEEE International Conference on Data Mining (ICDM). [paper]
  22. Fang, Y., Cheng, R., Tang, W., Maniu, S., & Yang, X. (2016). Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data . IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(3). [paper]
  23. Meng, C., Cheng, R., Maniu, S., Senellart, P., & Zhang, W. (2015). Discovering Meta-Paths in Large Heterogeneous Information Networks. World Wide Web Conference (WWW). [paper]
  24. Lei, S., Maniu, S., Mo, L., Cheng, R., & Senellart, P. (2015). Online Influence Maximization. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). [paper] [slides] [poster] [code]
  25. Spina, M., Rossi, D., Sozio, M., Maniu, S., & Cautis, B. (2015). Snooping Wikipedia Vandals with MapReduce. IEEE International Conference on Communications (ICC). [paper]
  26. Zheng, Y., Cheng, R., Maniu, S., & Mo, L. (2015). On Optimality of Jury Selection in Crowdsourcing. International Conference on Extending Database Technology (EDBT). [paper]
  27. Gouriten, G., Maniu, S., & Senellart, P. (2014). Scalable, Generic, and Adaptive Systems for Focused Crawling. ACM Hypertext Conference (HT). [paper]
  28. Giatsidis, C., Cautis, B., Maniu, S., Thilikos, D. M., & Vazirgiannis, M. (2014). Quantifying Trust Dynamics in Signed Graphs, the S-Cores Approach. SIAM International Conference on Data Mining (SDM). [paper]
  29. Cautis, B., & Maniu, S. (2013). Recherche top-k dépendant d’un contexte à l’aide de vues. Ingénierie Des Systèmes d’Information, 18(4).
  30. Maniu, S., & Cautis, B. (2013). Context-Aware Top-k Processing Using Views. ACM Conference on Information and Knowledge Management (CIKM). [paper] [slides]
  31. Maniu, S., & Cautis, B. (2013). Network-Aware Search in Collaborative Tagging Applications: Instance Optimality versus Efficiency. ACM Conference on Information and Knowledge Management (CIKM). [paper] [slides]
  32. Maniu, S., O’Hare, N., Aiello, L. M., Chiarandini, L., & Jaimes, A. (2013). Search Behaviour on Photo Sharing Platforms. IEEE International Conference on Multimedia and Expo (ICME). [paper]

Surveys, Tutorials, and Invited Papers

  1. Maniu, S., & Senellart, P. (2025). Database Theory in Action: Making Provenance and Probabilistic Database Theory Work in Practice. International Conference on Database Theory (ICDT). [paper]
  2. Amer-Yahia, S., Bogojeska, J., Facchinetti, R., Franceschi, V., Gionis, A., Hose, K., Koutrika, G., Kouyos, R., Lissandrini, M., Maniu, S., Mirylenka, K., Mottin, D., Palpanas, T., Rigotti, M., & Velegrakis, Y. (2025). Towards Reliable Conversational Data Analytics. International Conference on Extending Database Technology (EDBT). [paper]
  3. Bahri, M., Bifet, A., Gama, J., Gomes, H. M., & Maniu, S. (2021). Data Stream Analysis: Foundations, Major Tasks and Tools. WIREs Data Mining and Knowledge Discovery, 11(3).
  4. Bahri, M., Bifet, A., Maniu, S., & Gomes, H. M. (2020). Survey on Feature Transformation Techniques for Data Streams. International Joint Conference on Artificial Intelligence (IJCAI) . [paper]
  5. Cautis, B., Maniu, S., & Tziortziotis, N. (2019). Adaptive Influence Maximization. [slides]
  6. Amarilli, A., Maniu, S., & Monet, M. (2016). Challenges for Efficient Query Evaluation on Structured Probabilistic Data. International Conference on Scalable Uncertainty Management (SUM) . [paper]
  7. Amarilli, A., Maniu, S., & Senellart, P. (2015). Intensional Data on the Web. SIGWEB Newsletter. [paper]

Workshops, Posters, Demonstrations

  1. Gany, A., Maniu, S., & Cautis, B. (2026). Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraints. VLDB Workshop on Databases and Artificial Intelligence (DBAI). [paper]
  2. Groudiev, A., Saha, A., & Maniu, S. (2025). Extending Layer-wise Relevance Propagation in Neural Networks using Semiring Annotations. ProvenanceWeek (PW). [paper]
  3. Fares, A., Troullinou, G., Maniu, S., & Amer-Yahia, S. (2025). Optimizing Source Selection for Tuple-Value Discovery. VLDB International Workshop on Tabular Data Analysis (TaDa). [paper]
  4. Ramusat, Y., Maniu, S., & Senellart, P. (2022). Efficient Provenance-Aware Querying of Graph Databases with Datalog . ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems and Network Data Analytics (GRADES-NDA). [paper]
  5. Senellart, P., Jachiet, L., Maniu, S., & Ramusat, Y. (2018). ProvSQL: Provenance and Probability Management in PostgreSQL. Proceedings of the VLDB Endowment (PVLDB), 11(12). [paper]
  6. Ramusat, Y., Maniu, S., & Senellart, P. (2018). Semiring Provenance over Graph Databases. USENIX Workshop on the Theory and Practice of Provenance (TaPP). [paper]
  7. Fang, Y., Cheng, R., Tang, W., Maniu, S., & Yang, X. (2016). Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data . IEEE International Conference on Data Engineering (ICDE). [paper]
  8. Bifet, A., Maniu, S., Qian, J., Tian, G., He, C., & Fan, W. (2015). StreamDM: Advanced Data Mining in Spark Streaming. IEEE International Conference on Data Mining (ICDM). [paper]
  9. Lei, S., Yang, X. S., Mo, L., Maniu, S., & Cheng, R. (2014). iTag: Incentive-Based Tagging. IEEE International Conference on Data Engineering (ICDE). [paper] [poster]
  10. Maniu, S., & Cautis, B. (2012). Taagle: Efficient, Personalized Search in Collaborative Tagging Networks. ACM SIGMOD Conference on the Management of Data. [paper]
  11. Maniu, S., Abdessalem, T., & Cautis, B. (2011). Casting a Web of Trust over Wikipedia: An Interaction-Based Approach. Proceedings of the 20th International World Wide Web Conference (WWW). [paper]
  12. Maniu, S., Cautis, B., & Abdessalem, T. (2011). Building a Signed Network from Interactions in Wikipedia. First ACM SIGMOD Workshop on Databases and Social Networks (DBSocial). [paper]

Theses

  1. Maniu, S. (2022). Graphs and Uncertainty [PhD thesis]. Université Paris-Saclay. [paper]
  2. Maniu, S. (2012). Data Management in Social Networks [PhD thesis]. Télécom Paris. [paper]

Informal Publications and Pre-prints

  1. Sen, A., Maniu, S., & Senellart, P. (2025). ProvSQL: A General System for Keeping Track of the Provenance and Probability of Data.
  2. Colin, J., & Maniu, S. (2024). Optimizing Diverse Information Exposure in Social Graphs.
  3. John, P. G., Bhattacharyya, A., Maniu, S., Myrisiotis, D., & Wu, Z. (2024). Efficient, Low-Regret, Online Reinforcement Learning for Linear MDPs . [preprint]
  4. Ramusat, Y., Maniu, S., & Senellart, P. (2021). A Practical Dynamic Programming Approach to Datalog Provenance Computation. [preprint]
  5. Maniu, S., Senellart, P., & Jog, S. (2018). Une étude expérimentale de la largeur d’arbre de données graphe du monde réel.
  6. Lagrée, P., Cappé, O., Cautis, B., & Maniu, S. (2017). Maximisation en ligne et à grande échelle de l’influence sur les réseaux sociaux.
  7. Maniu, S., Cheng, R., & Senellart, P. (2014). ProbTree: A Query-Efficient Representation of Probabilistic Graphs.
  8. Gouriten, G., Maniu, S., & Senellart, P. (2013). Exploration adaptative des graphes sous contrainte de budget.
  9. Maniu, S., & Cautis, B. (2012). Context-aware top-k processing using views.
  10. Abdessalem, T., Cautis, B., & Maniu, S. (2011). Algorithme top-k pour la recherche d’informations dans les ré seaux sociaux.