- 29
- 29
- 20
- 4
- 4
- 2
- 2
- 2
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
Marc Plantevit
100
Documents
Researcher identifiers
marc-plantevit-
0000-0003-4636-5753
- IdRef : 125705328
Presentation
Full Professor
- EPITA
- LRDE
- <https://www.lrde.epita.fr/wiki/User:Marc>
Associate Professor (Maître de Conférences)
- Université Claude Bernard Lyon 1, Computer Science Departement
- LIRIS - UMR 5205
- Data Mining and Machine Learning research group (DM2L)
- <http://liris.cnrs.fr/~mplantev>
Publications
- 8
- 5
- 4
- 4
- 3
- 3
- 3
- 3
- 3
- 3
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 40
- 24
- 17
- 17
- 14
- 12
- 10
- 8
- 7
- 7
- 6
- 6
- 6
- 5
- 5
- 4
- 4
- 4
- 4
- 4
- 4
- 4
- 3
- 3
- 3
- 3
- 3
- 3
- 3
- 3
- 3
- 3
- 3
- 3
- 3
- 3
- 3
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 5
- 2
- 2
- 2
- 2
- 2
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 66
- 18
- 5
- 5
- 4
- 2
- 1
- 1
- 3
- 6
- 3
- 4
- 9
- 4
- 4
- 6
- 10
- 8
- 4
- 3
- 5
- 6
- 6
- 6
- 6
- 4
- 2
|
|
DiffVersify: a Scalable Approach to Differentiable Pattern Mining with Coverage RegularizationMachine Learning and Knowledge Discovery in Databases, Sep 2024, Vilnius, Lithuania. pp.407 - 422, ⟨10.1007/978-3-031-70365-2_24⟩
Conference papers
hal-04716579v1
|
|
|
Forecasting Electricity Prices: An Optimize Then Predict-Based ApproachIntelligent Data Analysis 2023, Apr 2023, Louvain-la_Neuve, Belgium. pp.446-458, ⟨10.1007/978-3-031-30047-9_35⟩
Conference papers
hal-04114222v1
|
|
|
Mining Java Memory Errors using Subjective Interesting Subgroups with Hierarchical TargetsIEEE International Conference on Data Mining Workshops (ICDM Workshops), IEEE, Dec 2023, Shanghai (Chine), China. ⟨10.1109/ICDMW60847.2023.00159⟩
Conference papers
hal-04224279v1
|
|
|
Découverte de sous-groupes de prédictions interprétables pour le triage d'incidentsExtraction et Gestion des Connaissances (EGC'2022), Jan 2022, Blois, France
Conference papers
hal-03627854v1
|
|
|
Qu'est-ce que mon GNN capture vraiment ? Exploration des représentations internes d'un GNNExtraction et Gestion des Connaissances (EGC 2022), Jan 2022, Blois, France. pp.159-170
Conference papers
hal-03921033v1
|
|
|
What Does My GNN Really Capture? On Exploring Internal GNN RepresentationsInternational Joint Conference on Artificial Intelligence 2022, Jul 2022, Vienna, Austria
Conference papers
hal-03700710v1
|
|
|
Gibbs Sampling Subjectively Interesting TilesAdvances in Intelligent Data Analysis {XVIII} - 18th International Symposium on Intelligent Data Analysis (IDA 2020), Apr 2020, Konstanz (on line), Germany. ⟨10.1007/978-3-030-44584-3_7⟩
Conference papers
hal-02960847v1
|
Why Should I Trust This Item? Explaining the Recommendations of any ModelIEEE International Conference on Data Science and Advanced Analytics (DSAA), Oct 2020, Sydney, Australia. ⟨10.1109/DSAA49011.2020.00067⟩
Conference papers
hal-02965196v1
|
|
|
|
Recommandation séquentielle à base de séquences fréquentesExtraction et Gestion des Connaissances (EGC), Jan 2019, Metz, France
Conference papers
hal-02914391v1
|
|
|
Analyse de comportements relatifs exceptionnels expliquée par des textes : les votes du parlement européenExtraction et Gestion des connaissances (EGC), Jan 2019, Metz, France. pp.437--440
Conference papers
hal-02009172v1
|
|
|
DEvIANT : Discovering significant exceptional (dis)agreement within groupsJoint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2019), Sep 2019, Würzburg, Germany. pp.3-20, ⟨10.1007/978-3-030-46150-8_1⟩
Conference papers
hal-02961093v1
|
|
|
FSSD - A Fast and Efficient Algorithm for Subgroup Set DiscoveryIEEE International Conference on Data Science and Advanced Analytics (DSAA), Oct 2019, Washington DC, United States. ⟨10.1109/DSAA.2019.00023⟩
Conference papers
hal-02355503v1
|
|
|
Contrastive antichains in hierarchiesSIGKDD 2019, Aug 2019, Anchorage, Alaska, United States. pp.294:304, ⟨10.1145/3292500.3330954⟩
Conference papers
hal-02114775v1
|
|
|
Exceptional Attributed Subgraph Mining To Understand The Olfactory Percept21st International Conference on Discovery Science, Oct 2018, Limassol, Cyprus. pp.276--291
Conference papers
hal-01878375v1
|
|
|
Mining Subjectively Interesting Attributed SubgraphsINTERNATIONAL WORKSHOP ON MINING AND LEARNING WITH GRAPHS, held with SIGKDD 2018, Aug 2018, Londres, United Kingdom
Conference papers
hal-02060190v1
|
|
|
Flash points: Discovering exceptional pairwise behaviors in vote or rating dataECML/PKDD, Sep 2017, Skopje, Macedonia. pp.442-458, ⟨10.1007/978-3-319-71246-8_27⟩
Conference papers
hal-01587041v1
|
|
|
Contextual Subgraph Discovery With Mobility ModelsCOMPLEX NETWORKS 2017, Nov 2017, Lyon, France. pp.477-489
Conference papers
hal-01625068v1
|
|
|
Local subgroup discovery for eliciting and understanding new structure-odor relationshipsDiscovery Science: 19th International Conference, DS 2016, Oct 2016, Bari, Italy. pp.19-34, ⟨10.1007/978-3-319-46307-0_2⟩
Conference papers
hal-01346660v1
|
|
|
h(odor): Interactive Discovery of Hypotheses on the Structure-Odor Relationship in NeuroscienceECML/PKDD 2016 (Demo), Sep 2016, Riva del Garda, Italy. pp.17--21
Conference papers
hal-01346679v1
|
|
|
Unsupervised Exceptional Attributed Sub-graph Mining in Urban DataIEEE International Conference on Data Mining (ICDM 2016), Dec 2016, Barcelone, Spain. pp.21-30
Conference papers
hal-01430622v1
|
|
|
Une méthode de découverte de motifs contextualisés dans les traces de mobilité d'une personne16ème Journées Francophones Extraction et Gestion des Connaissances, Jan 2016, Reims, France. pp.63-68
Conference papers
hal-01265204v1
|
Évaluation des performances réelles de double-peaux PV ventilées en milieu urbain suivant une approche orientée données2e journées nationales de l’énergie solaire - JNES 2015, Jul 2015, Perpignan, France
Conference papers
hal-01479040v1
|
|
|
|
Data-driven performance evaluation of ventilated photovoltaic double-skin facades in the built environment6th International Building Physics Conference, Jun 2015, Turin, Italy. pp.447-452, ⟨10.1016/j.egypro.2015.11.694⟩
Conference papers
hal-01272611v1
|
Fouille de données pour l’analyse du comportement complexe de systèmes photovoltaïque-thermiques en vrai grandeur et in situ intégrés aux bâtimentsCongrès français de thermique, la thermique de l'habitat et de la ville, May 2015, La Rochelle, France
Conference papers
hal-01478948v1
|
|
|
|
Profiling users of the Vélo 'v bike sharing system2nd International Workshop on Mining Urban Data (MUD), Ioannis Katakis, François Schnitzler, Thomas Liebig, Dimitrios Gunopulos, Katharina Morik,Gennady L. Andrienko, Shie Mannor, Jul 2015, Lille, France. pp.63-64
Conference papers
hal-01193017v1
|
Gazouille: Detecting and Illustrating Local Events from Geolocalized Social Media StreamsEuropean Conference on Machine Learning and Knowledge Discovery in Databases, 2015, Porto, Portugal. pp.276-280, ⟨10.1007/978-3-319-23461-8_29⟩
Conference papers
hal-01193030v1
|
|
Evaluation des performances réelles de double‑peaux PV ventilées en milieu urbain suivant une approche orientée données,XIIe Colloque Inter-Universitaire Franco-Québécois, Jun 2015, Sherbrooke, Canada. pp.01-09
Conference papers
hal-01478901v1
|
|
|
|
Vers la découverte de modèles exceptionnels locaux : des règles descriptives liant les molécules à leurs odeurs15e Journées Internationales Francophones Extraction et Gestion des Connaissances (EGC 2015), Jan 2015, Luxembourg, Luxembourg. pp.305-316
Conference papers
hal-01346739v1
|
Granularité des motifs de co-variation dans des graphes attribués dynamiques.Extraction et Gestion des Connaissances EGC 2014, Jan 2014, Rennes, France. pp.431-442
Conference papers
hal-01270736v1
|
|
|
|
Sequence Classification Based on Delta-Free Sequential PatternIEEE International Conference on Data Mining, Dec 2014, Shenzhen, China
Conference papers
hal-01100929v1
|
|
|
A Method for Characterizing Communities in Dynamic Attributed Complex NetworksIEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM), Aug 2014, Pékin, China. pp.481-484, ⟨10.1109/ASONAM.2014.6921629⟩
Conference papers
hal-01011913v1
|
Triggering Patterns of Topology Changes in Dynamic GraphsThe 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Aug 2014, Beijing, China, China. pp.55:1--55:17, ⟨10.1109/ASONAM.2014.6921577⟩
Conference papers
hal-01301075v1
|
|
|
|
Une méthode pour caractériser les communautés des réseaux dynamiques à attributs14ème Conférence Extraction et Gestion des Connaissances (EGC), Jan 2014, Rennes, France. pp.101-112
Conference papers
hal-00918181v1
|
Granularity of co-Evolution Patterns in Dynamic Attributed GraphsThe Thirteenth International Symposium on Intelligent Data Analysis IDA 2014, Oct 2014, Leuven, Belgium. pp.84-95
Conference papers
hal-01301086v1
|
|
Temporal Dependency Detection Between Interval-Based Event SequencesNew Frontiers in Mining Complex Patterns - Third International Workshop, NFMCP, Held in Conjunction with ECML-PKDD, Nancy, France, Revised Selected Papers, Sep 2014, Nancy, France. pp.132--146
Conference papers
hal-01979495v1
|
|
When TEDDY meets GrizzLY: Temporal Dependency Discovery for Triggering Road Deicing Operations (Demo)KDD, Aug 2013, Chicago, IL, United States. pp.1490-1493 ⟨10.1145/2487575.2487706⟩
Conference papers
hal-01339189v1
|
|
Trend Mining in Dynamic Attributed GraphsMachine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Sep 2013, Prague, Czech Republic. pp.654-669, ⟨10.1007/978-3-642-40988-2_42⟩
Conference papers
hal-01339225v1
|
|
Cohesive Co-Evolution Patterns in Dynamic Attributed GraphsDiscovery Science - 15th International Conference (DS 2012), Oct 2012, Lyon France. pp.110-124, ⟨10.1007/978-3-642-33492-4_11⟩
Conference papers
hal-01353051v1
|
|
Mining Disjunctive Rules in Dynamic Graphs2012 IEEE RIVF International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), Feb 2012, Ho Chi Minh, Vietnam. pp.74-79, ⟨10.1109/rivf.2012.6169829⟩
Conference papers
hal-01352944v1
|
|
Extraction de co-variations entre des propriétés de sommets et leur position topologique dans un graphe attribué.Actes Extraction et Gestion de Connaissances EGC'12, Jan 2012, Bordeaux, France. pp.267-278
Conference papers
hal-01352957v1
|
|
Mining Dominant Patterns in the SkyThe 11th IEEE International Conference on Data Mining - ICDM 2011, Dec 2011, Vancouver, B.C, Canada
Conference papers
inria-00623566v1
|
|
Extraction sous Contraintes d'Ensembles de Cliques Homogènes11eme Conference Francophone sur l'Extraction et la Gestion des Connaissances (EGC'11), 2011, Brest, France. pp.1-12
Conference papers
hal-00744808v1
|
|
Multidimensional Association Rules in Boolean Tensors11th SIAM International Conference on Data Mining SDM'11, Apr 2011, Phoenix, Arizona, United States. pp.570-581, ⟨10.1137/1.9781611972818.49⟩
Conference papers
hal-01354377v1
|
|
|
|
Summarizing Contrasts by Recursive Pattern MiningIEEE 11th International Conference on Data Mining Workshops (ICDMW), Dec 2011, Vancouver, Canada. pp.1155-1162, ⟨10.1109/ICDMW.2011.161⟩
Conference papers
hal-01021980v1
|
Motifs séquentiels δ-libresExtraction et gestion des connaissances (EGC'2011), Ali Khenchaf, Pascal Poncelet, Jan 2011, Brest, France
Conference papers
hal-00653579v1
|
|
|
|
Recursive Sequence Mining to Discover Named Entity Relations9th International Symposium on Intelligent Data Analysis (IDA'10), May 2010, Tucson, Arizona, United States, United States. pp.30-41
Conference papers
hal-01016928v1
|
|
|
Sequential Patterns to Discover and Characterise Biological Relations11th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing'10), Mar 2010, Iasi, Romania, Romania. pp.537-548
Conference papers
hal-01017207v1
|
Constraint-Based Mining of Sets of Cliques Sharing Vertex PropertiesWorkshop on Analysis of Complex NEtworks ACNE'10 co-located with ECML PKDD 2010, Sep 2010, Barcelona, Spain. pp.48-62
Conference papers
hal-01381539v1
|
|
Discovering Inter-Dimensional Rules in Dynamic GraphsWorkshop on Dynamic Networks and Knowledge Discovery DyNaK'10 co-located with ECML PKDD 2010, Sep 2010, Barcelona, Spain, Spain. pp.1-12
Conference papers
hal-01381535v1
|
|
|
|
Multidimensional Data Streams Summarization Using Extended Tilted-Time WindowsFINA: Frontiers of Information Systems and Network Applications, May 2009, Bradford, United Kingdom. pp.102-106, ⟨10.1109/WAINA.2009.145⟩
Conference papers
lirmm-00426480v1
|
Motifs séquentiels pour l'extraction d'information : illustration sur le problème de la détection d'interactions entre gènesActes de la 16ème conférence Traitement Automatique des Langues Naturelles (TALN'09), 2009, France
Conference papers
hal-01012300v1
|
|
|
|
Condensed Representation of Sequential Patterns according to Frequency-based Measures8th International Symposium on Intelligent Data Analysis (IDA'09), Sep 2009, Lyon, France, France. pp.155-166
Conference papers
hal-01011587v1
|
|
|
Fouille de données multidimensionnelles : différentes stratégies pour prendre en compte la mesureEDA: Entrepôts de Données et l'Analyse en ligne, Jun 2008, Toulouse, France. pp.61-76
Conference papers
hal-00283433v1
|
|
|
Fenêtres sur cubesBDA: Bases de Données Avancées, Oct 2008, Guilherand-Granges, France
Conference papers
lirmm-00324487v1
|
|
|
Up and Down: Mining Multidimensional Sequential Patterns Using HierarchiesDaWaK 2008 - 10th International Conference on Data Warehousing and Knowledge Discovery, Sep 2008, Turin, Italy. pp.156-165, ⟨10.1007/978-3-540-85836-2_15⟩
Conference papers
hal-00283442v1
|
|
|
Mining Multidimensional Sequential Patterns over Data StreamsDaWaK 2008 - 10th International Conference on Data Warehousing and Knowledge Discovery, Sep 2008, Turin, Italy. pp.263-272, ⟨10.1007/978-3-540-85836-2_25⟩
Conference papers
lirmm-00324432v1
|
|
|
Mining Unexpected Multidimensional RulesDOLAP: Data Warehousing and OLAP, Nov 2007, Lisbonne, Portugal. pp.89-96, ⟨10.1145/1317331.1317347⟩
Conference papers
lirmm-00175246v1
|
|
|
Extraction de Motifs Séquentiels Multidimensionnels Clos sans Gestion d'Ensemble de CandidatsEGC: Extraction et Gestion des Connaissances, Jan 2007, Nice, France
Conference papers
lirmm-00199036v1
|
Quelle partition pour les motifs séquentiels multidimensionnels ?LFA'07 : Rencontres Francophones sur la Logique Floue et ses Applications, pp.8
Conference papers
lirmm-00196961v1
|
|
|
|
HYPE : Prise en compte des hiérarchies lors de l'extraction de motifs séquentiels multidimensionnelsEDA'06 : Entrepôts de Données et Analyse en ligne, Jun 2006, Versailles, France, pp.155-176
Conference papers
lirmm-00135025v1
|
|
|
HYPE: Mining Hierarchical Sequential PatternsDOLAP'06: ACM Ninth International Workshop on Data Warehousing and OLAP, Nov 2006, Arlington, VA, USA, pp.8
Conference papers
lirmm-00135019v1
|
|
|
Motifs Séquentiels Multidimensionnels EtoilésBDA: Bases de Données Avancées, Oct 2005, Saint-Malo, France
Conference papers
lirmm-00106086v1
|
|
|
M2SP: Mining Sequential Patterns Among Several DimensionsPKDD 2005 - 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Oct 2005, Porto, Portugal. pp.205-216, ⟨10.1007/11564126_23⟩
Conference papers
lirmm-00106087v1
|
Local Pattern Detection in Attributed GraphsSolving Large Scale Learning Tasks. Challenges and Algorithms - Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday, pp.168-183, 2016, ⟨10.1007/978-3-319-41706-6_8⟩
Book sections
hal-02016506v1
|
|
|
Discovering and Visualizing Tactics in a Table Tennis Game Based on Subgroup DiscoveryECML/PKDD 2022 Workshop, Grenoble, France, 2022, ⟨10.1007/978-3-031-27527-2_8⟩
Other publications
hal-03768114v1
|
|
|
Extraction De Motifs Séquentiels Dans Des Données MultidimensionellesInformatique [cs]. Université Montpellier II - Sciences et Techniques du Languedoc, 2008. Français. ⟨NNT : ⟩
Theses
tel-00319242v1
|
|
|
Contributions to Pattern Mining in Augmented GraphsArtificial Intelligence [cs.AI]. Université Claude Bernard Lyon 1, 2018
Accreditation to supervise research
tel-01956252v1
|
|
|
Identifying exceptional (dis)agreement between groups - Technical Report[Research Report] LIRIS UMR CNRS 5205. 2019
Reports
hal-02018813v2
|
|
|
DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups[Research Report] LIRIS UMR CNRS 5205. 2019
Reports
hal-02161309v3
|
Mining CLosed Multidimensional Sequential Patterns06045, 2006, 10 p
Reports
lirmm-00102867v1
|
|
|
|
HYPE: Mining Hierarchical Sequential Patterns06046, 2006, 8 p
Reports
lirmm-00102862v1
|