Bibliography

Major publications by the team in recent years

• 1A. Affouard, H. Goëau, P. Bonnet, J.-C. Lombardo, A. Joly.
  Pl@ntNet app in the era of deep learning, in: ICLR: International Conference on Learning Representations, Toulon, France, April 2017, pp. 1-6.
  https://hal.archives-ouvertes.fr/hal-01629195
• 2T. Allard, G. Hébrail, F. Masseglia, E. Pacitti.
  Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series Clustering, in: 34th International ACM Conference on Management of Data (ACM SIGMOD), Melbourne, Australia, ACM SIGMOD, May 2015. [ DOI : 10.1145/2723372.2749453 ]
  https://hal.inria.fr/hal-01136686
• 3A. Joly, P. Bonnet, H. Goëau, J. Barbe, S. Selmi, J. Champ, S. Dufour-Kowalski, A. Affouard, J. Carré, J.-F. Molino, N. Boujemaa, D. Barthélémy.
  A look inside the Pl@ntNet experience, in: Multimedia Systems, 2015, 16 p. [ DOI : 10.1007/s00530-015-0462-9 ]
  https://hal.inria.fr/hal-01182775
• 4A. Joly, O. Buisson.
  Random Maximum Margin Hashing, in: CVPR'11 - IEEE Computer Vision and Pattern Recognition, Colorado springs, United States, IEEE, June 2011, pp. 873-880. [ DOI : 10.1109/CVPR.2011.5995709 ]
  https://hal.inria.fr/hal-00642178
• 5A. Joly, H. Goeau, P. Bonnet, V. Bakic, J. Barbe, S. Selmi, I. Yahiaoui, J. Carré, E. Mouysset, J.-F. Molino, N. Boujemaa, D. Barthélémy.
  Interactive plant identification based on social image data, in: Ecological Informatics, 2013. [ DOI : 10.1016/j.ecoinf.2013.07.006 ]
  http://www.sciencedirect.com/science/article/pii/S157495411300071X
• 6B. Kolev, P. Valduriez, C. Bondiombouy, R. Jiménez-Peris, R. Pau, J. O. Pereira.
  CloudMdsQL: Querying Heterogeneous Cloud Data Stores with a Common Language, in: Distributed and Parallel Databases, December 2016, vol. 34, n^o 4, pp. 463-503. [ DOI : 10.1007/s10619-015-7185-y ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01184016
• 7M. Liroz-Gistau, R. Akbarinia, D. Agrawal, P. Valduriez.
  FP-Hadoop: Efficient Processing of Skewed MapReduce Jobs, in: Information Systems, 2016, vol. 60, pp. 69-84. [ DOI : 10.1016/j.is.2016.03.008 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01377715
• 8J. Liu, E. Pacitti, P. Valduriez, D. De Oliveira, M. Mattoso.
  Multi-Objective Scheduling of Scientific Workflows in Multisite Clouds, in: Future Generation Computer Systems, 2016, vol. 63, pp. 76–95. [ DOI : 10.1016/j.future.2016.04.014 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01342203
• 9H. Lustosa, F. Porto, P. Blanco, P. Valduriez.
  Database System Support of Simulation Data, in: Proceedings of the VLDB Endowment (PVLDB), September 2016, vol. 9, n^o 13, pp. 1329-1340.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01363738
• 10S. Mahboubi, R. Akbarinia, P. Valduriez.
  Privacy-Preserving Top-k Query Processing in Distributed Systems, in: Euro-Par: European Conference on Parallel and Distributed Computing, Turin, Italy, August 2018, vol. LNCS, n^o 11014. [ DOI : 10.1007/978-3-319-96983-1_20 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01886160
• 11E. Pacitti, R. Akbarinia, M. El Dick.
  P2P Techniques for Decentralized Applications, Morgan & Claypool Publishers, 2012, 104 p.
  http://hal.inria.fr/lirmm-00748635
• 12C. Sahin, T. Allard, R. Akbarinia, A. Abbadi, E. Pacitti.
  A Differentially Private Index for Range Query Processing in Clouds, in: ICDE: International Conference on Data Engineering, Paris, France, April 2018.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01886725
• 13S. Salah, R. Akbarinia, F. Masseglia.
  Fast Parallel Mining of Maximally Informative k-Itemsets in Big Data, in: IEEE International Conference on Data Mining (ICDM), Atlantic city, United States, August 2015.
  http://hal-lirmm.ccsd.cnrs.fr/lirmm-01187275
• 14S. Salah, R. Akbarinia, F. Masseglia.
  A Highly Scalable Parallel Algorithm for Maximally Informative k-Itemset Mining, in: Knowledge and Information Systems (KAIS), January 2017.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01288571
• 15S. Salah, R. Akbarinia, F. Masseglia.
  Data placement in massively distributed environments for fast parallel mining of frequent itemsets, in: Knowledge and Information Systems (KAIS), 2017, vol. 53, n^o 1, pp. 207-237. [ DOI : 10.1007/s10115-017-1041-5 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620383
• 16M. Servajean, R. Akbarinia, E. Pacitti, S. Amer-Yahia.
  Profile Diversity for Query Processing using User Recommendations, in: Information Systems, March 2015, vol. 48, pp. 44-63. [ DOI : 10.1016/j.is.2014.09.001 ]
  http://hal-lirmm.ccsd.cnrs.fr/lirmm-01079523
• 17M. Servajean, A. Joly, D. Shasha, J. Champ, E. Pacitti.
  Crowdsourcing Thousands of Specialized Labels: A Bayesian Active Training Approach, in: IEEE Transactions on Multimedia, June 2017, vol. 19, n^o 6, pp. 1376 - 1391. [ DOI : 10.1109/TMM.2017.2653763 ]
  https://hal.archives-ouvertes.fr/hal-01629149
• 18D. E. Yagoubi, R. Akbarinia, B. Kolev, O. Levchenko, F. Masseglia, P. Valduriez, D. Shasha.
  ParCorr: efficient parallel methods to identify similar time series pairs across sliding windows, in: Data Mining and Knowledge Discovery, September 2018, vol. 32, n^o 5, pp. 1481-1507. [ DOI : 10.1007/s10618-018-0580-z ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01886794
• 19D.-E. Yagoubi, R. Akbarinia, F. Masseglia, T. Palpanas.
  DPiSAX: Massively Distributed Partitioned iSAX, in: ICDM 2017: IEEE International Conference on Data Mining, New Orleans, United States, November 2017, pp. 1-6.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620125
• 20T. M. Özsu, P. Valduriez.
  Principles of Distributed Database Systems, third edition, Springer, 2011, 845 p.
  http://hal.inria.fr/hal-00640392/en

Publications of the year

Doctoral Dissertations and Habilitation Theses

• 21V. Silva.
  Analysis of raw data from multiple data sources during the execution of computational simulations, Universidade Federal de Rio de Janeiro, June 2018.
  https://hal-lirmm.ccsd.cnrs.fr/tel-01830211
• 22D.-E. Yagoubi.
  Massive distribution for indexing and mining time series, Université de Montpellier, March 2018.
  https://tel.archives-ouvertes.fr/tel-01945348
• 23M. Zitouni.
  Parallel Itemset Mining in Massively Distributed Environments, Université de Tunis El Manar ; Inria, December 2018.
  https://tel.archives-ouvertes.fr/tel-01953619

Articles in International Peer-Reviewed Journals

• 24C. Botella, A. Joly, P. Bonnet, P. P. Monestiez, F. Munoz.
  Species distribution modeling based on the automated identification of citizen observations, in: Applications in Plant Sciences, March 2018, vol. 6, n^o 2, pp. 1-11. [ DOI : 10.1002/aps3.1029 ]
  https://hal.umontpellier.fr/hal-01739481
• 25J. Camata, V. Silva, P. Valduriez, M. Mattoso, A. L. G. A. Coutinho.
  In situ visualization and data analysis for turbidity currents simulation, in: Computers & Geosciences, January 2018, vol. 110, pp. 23-31. [ DOI : 10.1016/j.cageo.2017.09.013 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620127
• 26E. Cano, D. Fitzgerald, A. Liutkus, M. D. Plumbley, F.-R. Stöter.
  Musical Source Separation: An Introduction, in: IEEE Signal Processing Magazine, 2018.
  https://hal.inria.fr/hal-01945345
• 27T.-W. Chen, L. C. Cabrera-Bosquet, S. Alvarez Prado, R. Perez, S. Artzet, C. Pradal, A. Coupel-Ledru, C. Fournier, F. Tardieu.
  Genetic and environmental dissection of biomass accumulation in multi-genotype maize canopies, in: Journal of Experimental Botany, August 2018. [ DOI : 10.1093/jxb/ery309 ]
  https://hal.inria.fr/hal-01895279
• 28P. Fernique, C. Pradal.
  AutoWIG: automatic generation of python bindings for C++ libraries, in: PeerJ Computer Science, 2018, vol. 4. [ DOI : 10.7717/peerj-cs.149 ]
  https://hal.inria.fr/hal-01756458
• 29J. Liu, E. Pacitti, P. Valduriez.
  A Survey of Scheduling Frameworks in Big Data Systems, in: International Journal of Cloud Computing, 2018, vol. 7, n^o 2, pp. 103-128.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01692229
• 30J. Liu, L. Pineda, E. Pacitti, A. Costan, P. Valduriez, G. Antoniu, M. Mattoso.
  Efficient Scheduling of Scientific Workflows using Hot Metadata in a Multisite Cloud, in: IEEE Transactions on Knowledge and Data Engineering, 2018, pp. 1-20. [ DOI : 10.1109/TKDE.2018.2867857 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01867717
• 31C. Pradal, S. Cohen-Boulakia, G. Heidsieck, E. Pacitti, F. Tardieu, P. Valduriez.
  Distributed Management of Scientific Workflows for High-Throughput Plant Phenotyping, in: ERCIM News, 2018, pp. 36-37.
  https://hal.inria.fr/hal-01948568
• 32Z. Rafii, A. Liutkus, F.-R. Stöter, S. Ioannis Mimilakis, D. Fitzgerald, B. Pardo.
  An Overview of Lead and Accompaniment Separation in Music, in: IEEE/ACM Transactions on Audio, Speech and Language Processing, 2018. [ DOI : 10.1109/TASLP.2018.2825440 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01766781
• 33M. Servajean, R. Chailan, A. Joly.
  Non-parametric Bayesian annotator combination, in: Information Sciences, April 2018, vol. 436-437, pp. 131-145. [ DOI : 10.1016/j.ins.2018.01.020 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01703020
• 34V. Silva, D. De Oliveira, P. Valduriez, M. Mattoso.
  DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance, in: Proceedings of the VLDB Endowment (PVLDB), August 2018, vol. 11, n^o 12, pp. 2082-2085.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01867887
• 35R. Souza, V. Silva, A. L. Coutinho, P. Valduriez, M. Mattoso.
  Data reduction in scientific workflows using provenance monitoring and user steering, in: Future Generation Computer Systems, 2018, pp. 1-21. [ DOI : 10.1016/j.future.2017.11.028 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01679967
• 36D. E. Yagoubi, R. Akbarinia, B. Kolev, O. Levchenko, F. Masseglia, P. Valduriez, D. Shasha.
  ParCorr: efficient parallel methods to identify similar time series pairs across sliding windows, in: Data Mining and Knowledge Discovery, September 2018, vol. 32, n^o 5, pp. 1481-1507. [ DOI : 10.1007/s10618-018-0580-z ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01886794

Articles in National Peer-Reviewed Journals

• 37S. Blangy, V. Lhoste, C. Arnal, J. Carré, A. Chapot, I. Chuine, G. Darmon, A. Joly, P. Monestiez, P. Bonnet.
  Au-delà de la collecte des données dans les projets de sciences citoyennes : ouvrir le champ de l’analyse et de l’interprétation des données aux citoyens, in: Technologie et innovation, 2018.
  https://hal.archives-ouvertes.fr/hal-01824900

Invited Conferences

• 38P. Valduriez, M. Mattoso, R. Akbarinia, H. Borges, J. Camata, A. L. G. A. Coutinho, D. Gaspar, N. Lemus, J. Liu, H. Lustosa, F. Masseglia, F. Nogueira Da Silva, V. Silva, R. Souza, K. Ocaña, E. Ogasawara, D. Oliveira, E. Pacitti, F. Porto, D. Shasha.
  Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project, in: LADaS: Latin America Data Science Workshop, Rio de Janeiro, Brazil, CEUR-WS.org, August 2018, vol. CEUR Workshop Proceedings, n^o 2170.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01867804

International Conferences with Proceedings

• 39M. R. Bouadjenek, E. Pacitti, M. Servajean, F. Masseglia, A. Abbadi.
  A Distributed Collaborative Filtering Algorithm Using Multiple Data Sources, in: DBKDA: Advances in Databases, Knowledge, and Data Applications, Nice, France, May 2018, https://arxiv.org/abs/1807.05853.
  https://hal.archives-ouvertes.fr/hal-01911684
• 40R. Campisano, H. Borges, F. Porto, F. Perosi, E. Pacitti, F. Masseglia, E. Ogasawara.
  Discovering Tight Space-Time Sequences, in: DaWaK: Data Warehousing and Knowledge Discovery, Regensburg, Germany, September 2018, vol. LNCS, n^o 11031, pp. 247-257. [ DOI : 10.1007/978-3-319-98539-8_19 ]
  https://hal.archives-ouvertes.fr/hal-01925965
• 41A. B. Cruz, J. Ferreira, D. Carvalho, E. Mendes, E. Pacitti, R. Coutinho, F. Porto, E. Ogasawara.
  Detecçao de Anomalias Frequentes no Transporte Rodoviario Urbano, in: SBBD: Simpósio Brasileiro de Banco de Dados, Rio de Janeiro, Brazil, SBC, August 2018, pp. 271-276.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01868597
• 42D. Di Carlo, A. Liutkus, K. Déguernel.
  Interference reduction on full-length live recordings, in: ICASSP 2018 - IEEE International Conference on Acoustics, Speech, and Signal Processing, Calgary, Canada, IEEE, April 2018, pp. 736-740. [ DOI : 10.1109/ICASSP.2018.8462621 ]
  https://hal.inria.fr/hal-01713889
• 43J. Ferreira, J. Soares, F. Porto, E. Pacitti, R. Coutinho, E. Ogasawara.
  Rumo à Integração da Álgebra de Workflows com o Processamento de Consulta Relacional, in: SBBD: Simpósio Brasileiro de Banco de Dados, Rio de Janeiro, Brazil, SBC, August 2018, pp. 205-210.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01868556
• 44M. Fontaine, F.-R. Stöter, A. Liutkus, U. Simsekli, R. Serizel, R. Badeau.
  Multichannel Audio Modeling with Elliptically Stable Tensor Decomposition, in: LVA ICA 2018 - 14th International Conference on Latent Variable Analysis and Signal Separation, Surrey, United Kingdom, July 2018.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01766795
• 45A. Joly, H. Goëau, C. Botella, H. Glotin, P. Bonnet, W.-P. Vellinga, R. Planqué, H. Müller.
  Overview of LifeCLEF 2018: A Large-Scale Evaluation of Species Identification and Recommendation Algorithms in the Era of AI, in: CLEF: Cross-Language Evaluation Forum, Avignon, France, Experimental IR Meets Multilinguality, Multimodality, and Interaction, September 2018, vol. LNCS, n^o 11018, pp. 247-266. [ DOI : 10.1007/978-3-319-98932-7_24 ]
  https://hal.archives-ouvertes.fr/hal-01913231
• 46N. Keriven, A. Deleforge, A. Liutkus.
  Blind Source Separation Using Mixtures of Alpha-Stable Distributions, in: ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Canada, IEEE, April 2018, pp. 771-775, https://arxiv.org/abs/1711.04460. [ DOI : 10.1109/ICASSP.2018.8462095 ]
  https://hal.inria.fr/hal-01633215
• 47B. Kolev, O. Levchenko, E. Pacitti, P. Valduriez, R. Vilaça, R. C. Gonçalves, R. Jiménez-Peris, P. Kranas.
  Parallel Polyglot Query Processing on Heterogeneous Cloud Data Stores with LeanXcale, in: IEEE BigData, Seattle, United States, IEEE, December 2018, 10 p.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01921718
• 48O. Levchenko, D.-E. Yagoubi, R. Akbarinia, F. Masseglia, B. Kolev, D. Shasha.
  Spark-parSketch: A Massively Distributed Indexing of Time Series Datasets, in: CIKM: Conference on Information and Knowledge Management, Turin, Italy, October 2018, pp. 1951-1954. [ DOI : 10.1145/3269206.3269226 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01886760
• 49J. Liu, N. Lemus, E. Pacitti, F. Porto, P. Valduriez.
  Computation of PDFs on Big Spatial Data: Problem & Architecture, in: LADaS: Latin America Data Science Workshop, Rio de Janeiro, Brazil, CEUR-WS.org, August 2018, vol. 2170, 6 p.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01867758
• 50A. Liutkus, C. Rohlfing, A. Deleforge.
  Audio source separation with magnitude priors: the BEADS model, in: ICASSP 2018 – IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Canada, Signal Processing and Artificial Intelligence: Changing the World, April 2018, pp. 1-5. [ DOI : 10.1109/ICASSP.2018.8462515 ]
  https://hal.inria.fr/hal-01713886
• 51S. Mahboubi, R. Akbarinia, P. Valduriez.
  Answering Top-k Queries over Outsourced Sensitive Data in the Cloud, in: DEXA: Database and Expert Systems Applications, Regensburg, Germany, September 2018, vol. LNCS, n^o 11029, pp. 218-231. [ DOI : 10.1007/978-3-319-98809-2_14 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01886164
• 52S. Mahboubi, R. Akbarinia, P. Valduriez.
  Privacy-Preserving Top-k Query Processing in Distributed Systems, in: Euro-Par: European Conference on Parallel and Distributed Computing, Turin, Italy, August 2018, pp. 281-292. [ DOI : 10.1007/978-3-319-96983-1_20 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01886160
• 53F. Porto, A. Khatibi, J. G. Rittmeyer, E. Ogasawara, P. Valduriez, D. Shasha.
  Constellation Queries over Big Data, in: SBBD: Simpósio Brasileiro de Banco de Dados, Rio de Janeiro, Brazil, SBC, August 2018, pp. 85-96.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01867833
• 54F. Porto, J. G. Rittmeyer, E. Ogasawara, A. Krone-Martins, P. Valduriez, D. Shasha.
  Point Pattern Search in Big Data, in: SSDBM: Scientific and Statistical Database Management, Bozen-Bolzano, Italy, ACM, July 2018. [ DOI : 10.1145/3221269.3221294 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01819290
• 55C. Sahin, T. Allard, R. Akbarinia, A. Abbadi, E. Pacitti.
  A Differentially Private Index for Range Query Processing in Clouds, in: ICDE: International Conference on Data Engineering, Paris, France, April 2018, pp. 857-868.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01886725
• 56D. Silva, A. Paes, E. Pacitti, D. De Oliveira.
  F ReeP: towards parameter recommendation in scientific workflows using preference learning, in: SBBD: Simpósio Brasileiro de Banco de Dados, Rio de Janeiro, Brazil, SBC, August 2018, n^o 211-216.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01868574
• 57U. Simsekli, H. Erdogan, S. Leglaive, A. Liutkus, R. Badeau, G. Richard.
  Alpha-stable low-rank plus residual decomposition for speech enhancement, in: ICASSP 2018 - IEEE International Conference on Acoustics, Speech, and Signal Processing, Calgary, Canada, April 2018.
  https://hal.inria.fr/hal-01714909
• 58F.-R. Stöter, A. Liutkus, N. Ito.
  The 2018 Signal Separation Evaluation Campaign, in: LVA ICA: Latent Variable Analysis and Signal Separation, Surrey, United Kingdom, July 2018.
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01766791
• 59D. Ward, R. D. Mason, C. Kim, F.-R. Stöter, A. Liutkus, M. D. Plumbley.
  SiSEC 2018: State of the art in musical audio source separation - subjective selection of the best algorithm, in: WIMP: Workshop on Intelligent Music Production, Huddersfield, United Kingdom, September 2018.
  https://hal.inria.fr/hal-01945362

Conferences without Proceedings

• 60B. Deneu, M. Servajean, C. Botella, A. Joly.
  Location-based species recommendation using co-occurrences and environment-GeoLifeCLEF 2018 challenge, in: CLEF: Conference and Labs of the Evaluation Forum, Avignon, France, September 2018, vol. CEUR Workshop Proceedings, n^o 2125.
  https://hal.archives-ouvertes.fr/hal-01913241
• 61H. Goëau, P. Bonnet, A. Joly.
  Overview of ExpertLifeCLEF 2018: how far automated identification systems are from the best experts?, in: CLEF: Conference and Labs of the Evaluation Forum, Avignon, France, September 2018.
  https://hal.archives-ouvertes.fr/hal-01913244
• 62B. Yun.
  How Can You Mend a Broken Inconsistent KBs in Existential Rules Using Argumentation, in: SSA: Summer School on Argumentation, Varsovie, Poland, September 2018.
  https://hal.archives-ouvertes.fr/hal-01940651
• 63M. Zitouni, R. Akbarinia, S. Ben Yahia, F. Masseglia.
  Maximally Informative k-Itemset Mining from Massively Distributed Data Streams, in: SAC: Symposium on Applied Computing, Pau, France, April 2018, pp. 1-10.
  https://hal.archives-ouvertes.fr/hal-01711990

Scientific Books (or Scientific Book chapters)

• 64P. Bonnet, H. Goëau, S. T. Hang, M. Lasseck, M. Sulc, V. V. Malécot, P. Jauzein, J.-C. Melet, C. You, A. Joly.
  Plant Identification: Experts vs. Machines in the Era of Deep Learning: Deep learning techniques challenge flora experts, in: Multimedia Tools and Applications for Environmental & Biodiversity Informatics, June 2018, vol. Chapter 8, pp. 131-149. [ DOI : 10.1007/978-3-319-76445-0_8 ]
  https://hal.archives-ouvertes.fr/hal-01913277
• 65C. Botella, A. Joly, P. Bonnet, P. Monestiez, F. Munoz.
  A deep learning approach to Species Distribution Modelling, in: Multimedia Tools and Applications for Environmental & Biodiversity Informatics, A. Joly, S. Vrochidis, K. Karatzas, A. Karppine, P. Bonne (editors), Springer, 2018, pp. 169-199. [ DOI : 10.1007/978-3-319-76445-0_10 ]
  https://hal.archives-ouvertes.fr/hal-01834227
• 66J. Carranza-Rojas, A. Joly, H. Goëau, E. Mata-Montero, P. Bonnet.
  Automated identification of herbarium specimens at different taxonomic levels, in: Multimedia Tools and Applications for Environmental & Biodiversity Informatics, June 2018, vol. Multimedia Systems and Applications, pp. 151-167. [ DOI : 10.1007/978-3-319-76445-0_9 ]
  https://hal.archives-ouvertes.fr/hal-01913272
• 67A. A. Nugraha, A. Liutkus, E. Vincent.
  Deep neural network based multichannel audio source separation, in: Audio Source Separation, Springer, March 2018.
  https://hal.inria.fr/hal-01633858
• 68B. Pardo, A. Liutkus, Z. Duan, G. Richard.
  Applying source separation to music, in: Audio Source Separation and Speech Enhancement, Wiley, August 2018, vol. Chapter 16. [ DOI : 10.1002/9781119279860.ch16 ]
  https://hal.inria.fr/hal-01945320

Books or Proceedings Editing

• 69A. Joly, S. Vrochidis, K. Karatzas, A. Karppinen, P. Bonnet (editors)
  Multimedia Tools and Applications for Environmental & Biodiversity Informatics, Springer International Publishing, 2018. [ DOI : 10.1007/978-3-319-76445-0 ]
  https://hal-lirmm.ccsd.cnrs.fr/lirmm-01959343

Internal Reports

• 70M. Contractor, C. Pradal, D. Shasha.
  Platform Migrator, New York University, May 2018, n^o TR2018-990, 43 p.
  https://hal.inria.fr/hal-01948552

Other Publications

• 71C. Botella, P. Bonnet, F. Munoz, P. P. Monestiez, A. Joly.
  Overview of GeoLifeCLEF 2018: location-based species recommendation, CEUR Workshops Proceedings, September 2018, vol. CEUR-WS, n^o 2125, CLEF: Cross-Language Evaluation Forum, Poster.
  https://hal.archives-ouvertes.fr/hal-01913238
• 72F. Reyes, B. Pallas, D. Gianelle, C. Pradal, F. Vaggi, D. Zanotelli, M. Tagliavini, D. Gianelle, E. Costes.
  MuSCA: a multi-scale model to explore carbon allocation in plants, October 2018, working paper or preprint. [ DOI : 10.1101/370189 ]
  https://hal.archives-ouvertes.fr/hal-01844390