Keys Words

Machine learning, learning theory, deep learning, representation learning, dictionary learning, spectral learning, bandits, kernel methods, grammatical inference


Hachem KADRI

Permanent Members

ARTIERES ThierryProfesseur des Universités
Courriel : thierry.artieres@lis-lab.fr
Telephone : 0486090478
Page personnelle : https://pageperso.lis-lab.fr/thierry.artieres/
AYACHE StéphaneMaitre de Conférences
Courriel : stephane.ayache@lis-lab.fr
Telephone : 0486090452
Page personnelle : https://pageperso.lis-lab.fr/stephane.ayache/
CAPPONI CécileMaitre de Conférences
Courriel : cecile.capponi@lis-lab.fr
Telephone : 0486090478
Page personnelle : https://pageperso.lis-lab.fr/cecile.capponi/
DUPÉ François-xavierMaitre de Conférences
Courriel : francois-xavier.dupe@lis-lab.fr
Telephone : 0486090478
EMIYA ValentinMaitre de Conférences
Courriel : valentin.emiya@lis-lab.fr
Telephone : 0486090486
Page personnelle : https://pageperso.lis-lab.fr/valentin.emiya/
EYRAUD RémiMaitre de Conférences
Courriel : remi.eyraud@lis-lab.fr
Telephone : 0486090466
Page personnelle : https://pageperso.lis-lab.fr/remi.eyraud/
KADRI HachemMaitre de Conférences
Courriel : hachem.kadri@lis-lab.fr
Telephone : 0486090475
Page personnelle : https://pageperso.lis-lab.fr/hachem.kadri/
RALAIVOLA LivaProfesseur des Universités
Courriel : liva.ralaivola@lis-lab.fr
Telephone : 0486090671
Page personnelle : https://pageperso.lis-lab.fr/liva.ralaivola/
SICRE RonanMaitre de Conférences
Courriel : ronan.sicre@lis-lab.fr

Phd Studients

BAUVIN BaptisteDoctorant
Courriel : baptiste.bauvin@lis-lab.fr
Courriel : leo.bouscarrat@lis-lab.fr
CHERFAOUI FarahDoctorant
Courriel : farah.cherfaoui@lis-lab.fr
DAGENS TomDoctorant
Courriel : tom.dagens@lis-lab.fr
ECM TestDoctorant
Courriel : test.ecm@lis-lab.fr
FERRE QuentinDoctorant
Courriel : quentin.ferre@lis-lab.fr
GIFFON LucDoctorant
Courriel : luc.giffon@lis-lab.fr
Page personnelle : https://pageperso.lis-lab.fr/luc.giffon/
GUO ZiyuDoctorant
Courriel : gzypb230@gmail.com
Telephone : 0491827647
HUUSARI RiikkaDoctorant
Courriel : riikka.huusari@lis-lab.fr
Telephone : 0486090478
Page personnelle : https://pageperso.lis-lab.fr/riikka.huusari/
KREME Ama-marinaDoctorant
Courriel : ama-marina.kreme@lis-lab.fr
QI WangDoctorant
Courriel : wang.qi@lis-lab.fr
Telephone : 0486090478
Page personnelle : https://pageperso.lis-lab.fr/wang.qi/
WANG QiqiDoctorant
Courriel : qiqi.wang@lis-lab.fr
Page personnelle : https://pageperso.lis-lab.fr/qiqi.wang/

Other staff members

Courriel : dominique.benielli@lis-lab.fr
DENIS FrançoisProfesseur des Universités Emerite
Courriel : francois.denis@lis-lab.fr
Telephone : 0486090478
Page personnelle : https://pageperso.lis-lab.fr/francois.denis/
KOCO SokolPost-Doctorant
Courriel : sokol.koco@lis-lab.fr
MILANESI PaoloPost-Doctorant
Courriel : paolo.milanesi@lis-lab.fr
SELLAMI AkremPost-Doctorant
Courriel : akrem.sellami@lis-lab.fr
VILLOUTREIX PaulPost-Doctorant
Courriel : paul.villoutreix@lis-lab.fr

Research interests

QARMA is the machine learning research team of “Laboratoire d’Informatique et Systèmes” (LIS). The team focuses on three major aspects of machine learning: learning theory, deep learning, and learning in the context of signal processing. QARMA is the to-go team of machine learning in certain theoretical aspects such as spectral learning, grammatical inference, operator-valued kernels, and generalization bounds. The approach to learning and signal processing is
enriched by collaborations with mathematicians from I2M and other laboratories.

The team promotes the benefit of research focused on both fundamental aspects and applications that generate original and challenging problems to investigate. QARMA is part of multiple theoretical and/or applied research projects. Some of the team’s favourite applications are neuroscience, bioinformatics, astrophysics, as well as music, multimedia, and time series.

The QARMA team was founded in 2012 and includes 10 permanent members and ten to fifteen doctoral students and post doctoral research fellows. In the LIS, Qarma belongs to the “pole Science des Données”. The team is primarily located in Chateau-Gombert. Some doctoral students are co-tutored with INT, CPPM, TAGC or University of Quebec.

Scientific publications

35 documents

Article dans une revue

  • Farah Cherfaoui, Valentin Emiya, Liva Ralaivola, Sandrine Anthoine. Recovery and convergence rate of the Frank-Wolfe Algorithm for the m-EXACT-SPARSE Problem. IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, In press. ⟨hal-01919761v2⟩
  • François-Xavier Dupé, Sandrine Anthoine. Generalized Greedy Alternatives. Applied and Computational Harmonic Analysis, Elsevier, 2018, ⟨10.1016/j.acha.2018.10.005⟩. ⟨hal-01431322v2⟩
  • Thierry Artières, Qi Wang, Mickaël Chen, Ludovic Denoyer. Adversarial learning for modeling human motion. Visual Computer, Springer Verlag, 2018, pp.1-20. ⟨10.1007/s00371-018-1594-7⟩. ⟨hal-01874144⟩
  • Jane Chandlee, Rémi Eyraud, Jeffrey Heinz, Adam Jardine, Jonathan Rawski. How the Structure of the Constraint Space Enables Learning. Proceedings of the Society for Computation in Linguistics, Gaja Jarosz, 2018, 2, pp.387-388. ⟨10.7275/0v66-q733⟩. ⟨hal-01958707⟩
  • Alain Rakotomamonjy, Sokol Koço, Liva Ralaivola. Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization. IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2017, 28 (11), pp.2789-2802. ⟨10.1109/TNNLS.2016.2600243⟩. ⟨hal-01774838⟩
  • François Laviolette, Emilie Morvant, Liva Ralaivola, Jean-Francis Roy. Risk upper bounds for general ensemble methods with an application to multiclass classification. Neurocomputing, Elsevier, 2017, 219, pp.15 - 25. ⟨10.1016/j.neucom.2016.09.016⟩. ⟨hal-01774837⟩

Communication dans un congrès

  • Riikka Huusari, Hachem Kadri. Entangled Kernels. International Joint Conference of Artificial Intelligence, Aug 2019, Macao, China. ⟨hal-02187162⟩
  • Luc Giffon, Stéphane Ayache, Thierry Artières, Hachem Kadri. Deep Networks with Adaptive Nyström Approximation. IJCNN 2019 - International Joint Conference on Neural Networks, Jul 2019, Budapest, Hungary. ⟨hal-02091661⟩
  • Riikka Huusari, Cécile Capponi, Hachem Kadri, Paul Villoutreix. Apprentissage multi-vues pour la complétion transmodale de matrices de noyaux. Conférence sur l'Apprentissage Automatique, Jul 2019, Toulouse, France. ⟨hal-02176625⟩
  • Onkar Pandit, Pascal Denis, Liva Ralaivola. Learning Rich Event Representations and Interactions for Temporal Relation Classification. ESANN 2019 - 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2019, Bruges, Belgium. ⟨hal-02265061⟩
  • Farah Cherfaoui, Valentin Emiya, Liva Ralaivola, Sandrine Anthoine. Frank-Wolfe Algorithm for the Exact Sparse Problem. iTWIST: international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, Nov 2018, Marseille, France. ⟨hal-01881329⟩
  • Ama Marina Kreme, Valentin Emiya, Caroline Chaux. Phase inpainting in time-frequency plane. iTWIST: international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, Nov 2018, Marseille, France. ⟨hal-01881334⟩
  • Ichrak Toumi, Valentin Emiya. Joint-sparse modeling for audio inpainting. iTWIST: international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, Nov 2018, Marseille, France. ⟨hal-01881338⟩
  • Stéphane Ayache, Rémi Eyraud, Noé Goudian. Explaining Black Boxes on Sequential Data using Weighted Automata. 14th International Conference on Grammatical Inference, Sep 2018, Wrocław,, Poland. ⟨hal-01888514⟩
  • Ama Marina Kreme, Valentin Emiya, Caroline Chaux. Phase reconstruction for time-frequency inpainting. International conference on Latent Variable Analysis and Signal Separation (LVA/ICA), Jul 2018, Guildford, United Kingdom. ⟨hal-01865467⟩
  • Riikka Huusari, Hachem Kadri. Intrication et noyaux à valeurs opérateurs. Conférence sur l'apprentissage automatique, Jun 2018, Rouen, France. ⟨hal-02072695⟩
  • Luc Giffon, Stéphane Ayache, Hachem Kadri, Thierry Artières. Deepström: ´ Emulsion de noyaux et d'apprentissage profond. CAp 2018 - Conférence sur l'Apprentissage Automatique, Jun 2018, Rouen, France. ⟨hal-02091648⟩
  • Konstantin Usevich, Valentin Emiya, David Brie, Caroline Chaux. Characterization of finite signals with low-rank STFT. IEEE Statistical Signal Processing Workshop, SSP 2018, Jun 2018, Freiburg, Germany. ⟨10.1109/SSP.2018.8450745⟩. ⟨hal-01717931v2⟩
  • Riikka Huusari, Hachem Kadri, Cécile Capponi. Support Vector Machine Framework for Multi-View Metric Learning. 50e Journées de Statistique de la Société Française de Statistique, May 2018, Paris, France. ⟨hal-02070699⟩
  • Mickaël Chen, Ludovic Denoyer, Thierry Artières. Multi-View Data Generation Without View Supervision. 6th International Conference on Learning Representations (ICLR 2018), Apr 2018, Vancouver, Canada. ⟨hal-02101404⟩
  • Qi Wang, Mickaël Chen, Thierry Artières, Ludovic Denoyer. Transferring Style in Motion Capture Sequences with Adversarial Learning. ESANN, Apr 2018, Bruges, Belgium. ⟨hal-02100672⟩
  • Valentin Emiya, Ronan Hamon, Caroline Chaux. Being low-rank in the time-frequency plane. ICASSP - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Canada. ⟨hal-01636111⟩
  • Ichrak Toumi, Valentin Emiya. Sparse non-local similarity modeling for audio inpainting. ICASSP - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Canada. ⟨hal-01680669⟩
  • Riikka Huusari, Hachem Kadri, Cécile Capponi. Multi-view Metric Learning in Vector-valued Kernel Spaces. The 21st International Conference on Artificial Intelligence and Statistics, Apr 2018, Lanzarote, Spain. ⟨hal-01736068⟩
  • Julien Audiffren, Liva Ralaivola. Bandits Dueling on Partially Ordered Sets. Neural Information Processing Systems, NIPS 2017, Dec 2017, Long Beach, CA, United States. ⟨hal-01774844⟩
  • Denis Arrivault, Dominique Benielli, François Denis, Rémi Eyraud. Scikit-SpLearn : a toolbox for the spectral learning of weighted automata compatible with scikit-learn. Conférence francophone sur l' Apprentissage Aurtomatique, Jun 2017, Grenoble, France. ⟨hal-01777169⟩
  • Thierry Artières, Gabriella Contardo, Ludovic Denoyer. Recurrent Neural Networks for Adaptive Feature Acquisition. 23rd International Conference on Neural Information Processing (ICONIP 2016), Oct 2016, Kyoto, Japan. pp.591-599, ⟨10.1007%2F978-3-319-46675-0_65⟩. ⟨hal-01874158⟩

Chapitre d'ouvrage

  • Cécile Capponi, Sokol Koço. Learning from Imbalanced Datasets with Cross-View Cooperation-Based Ensemble Methods. Springer. Linking and Mining Heterogeneous and Multi-view Data, 2019, 978-3-030-01872-6. ⟨hal-02068594⟩
  • Riikka Huusari, Hachem Kadri, Cécile Capponi. General Framework for Multi-View Metric Learning. Linking and Mining Heterogeneous and Multi-view Data, 2019. ⟨hal-02166731⟩

Pré-publication, Document de travail

  • Luc Giffon, Valentin Emiya, Liva Ralaivola, Hachem Kadri. QuicK-means: Acceleration of K-means by learning a fast transform. 2019. ⟨hal-02174845⟩
  • Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah, Sergio Escalera, Yagmur Gucluturk, et al.. Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos. 2019. ⟨hal-01991652⟩
  • Ichrak Toumi, Valentin Emiya. Audio inpainting based on joint-sparse modeling. 2019. ⟨hal-01928569⟩
  • Mickaël Chen, Ludovic Denoyer, Thierry Artières. Multi-View Data Generation Without View Supervision. 2018. ⟨hal-01689997⟩
  • Gabriella Contardo, Ludovic Denoyer, Thierry Artières. A Meta-Learning Approach to One-Step Active Learning. 2018. ⟨hal-01690004⟩
  • François-Xavier Dupé. Greed is Fine: on Finding Sparse Zeros of Hilbert Operators. 2015. ⟨hal-01120059v2⟩