Chaire Deep learner explanation & verification

Membres de la chaire
Références et publications
Membres de la chaire

Porteur : Joao, Marques-Silva (CNRS, IRIT)

Co-chairs :  

  • Martin Cooper (UT3, IRIT)
  • Emmanuel Hebrard (CNRS, LAAS)

Chercheurs associés :

  • Mohamed Siala (INSA Toulouse, LAAS)
  • Christian Bessiere (CNRS,LIRMM)

Doctorants :

  • Thomas Gerspacher, depuis avril 2020
  • Xuangxiang Huang, depuis novembre 2020

Post-docs : 

  • Yacine Izza, depuis april 2020

Chercheurs invités : 

  • Gianpiero Cabodi, Politecnico di Torino, Italy, Jan 26-28 2020

  • Daniel Gibert, University of Lleida, Spain, Jan-Apr 2020

Références et publications

[2021]: 6 A*, 2 A

  • [ICML21] Joao Marques-Silva, Thomas Gerspacher, Martin C. Cooper, Alexey Ignatiev, Nina Narodytska: Explanations for Monotonic Classifiers. ICML 2021. Preprint: https://arxiv.org/abs/2106.00154
  • [IJCAI21a] Yacine Izza, Joao Marques-Silva: On Explaining Random Forests with SAT. IJCAI 2021. Preprint: https://arxiv.org/abs/2105.10278
  • [IJCAI21b] Alexey Ignatiev, Joao Marques-Silva, Nina Narodytska, and Peter J. Stuckey: Reasoning- Based Learning of Interpretable ML Models. IJCAI 2021. Preprint: https://alexeyignatiev.github.io/assets/pdf/imsns-ijcai21-preprint.pdf
  • [AAAI21] Alexey Ignatiev, Edward Lam, Peter J. Stuckey, Joao Marques-Silva: A Scalable Two Stage Approach to Computing Optimal Decision Sets. AAAI 2021: 3806-3814 Paper: https://ojs.aaai.org/index.php/AAAI/article/view/16498
  • [KR21] Xuanxiang Huang, Yacine Izza, Alexey Ignatiev, Joao Marques-Silva: On Efficiently Explaining Graph-Based Classifiers. KR 2021. Preprint: https://arxiv.org/abs/2106.01350
  • [SAT21a] Alexey Ignatiev, Joao Marques-Silva: SAT-Based Rigorous Explanations for Decision Lists. SAT 2021.Preprint: https://arxiv.org/abs/2105.06782
  • [SAT21b] Stepan Kochemazov, Alexey Ignatiev, Joao Marques-Silva: Assessing Progress in SAT Solvers Through the Lens of Incremental SAT. SAT 2021. Preprint: https://alexeyignatiev.github.io/assets/pdf/kims-sat21-preprint.pdf
  • [DATE21] Gianpiero Cabodi, Paolo E. Camurati, Alexey Ignatiev, Joao Marques-Silva, Marco Palena, and Paolo Pasini. DATE 2021. Preprint: https://alexeyignatiev.github.io/assets/pdf/ccimspp-date21-preprint.pdf
  • [AIJ21] Martin C. Cooper, Andreas Herzig, Faustine Maffre, Frédéric Maris, Elise Perrotin, Pierre Régnier : A lightweight epistemic logic and its application to planning. Artificial Intelligence, 298 (2021).

[2020]: 6 A*, 7 A

  • [NIPS20] Joao Marques-Silva, Thomas Gerspacher, Martin C. Cooper, Alexey Ignatiev, Nina Narodytska: Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay. NeurIPS 2020. Paper: https://proceedings.neurips.cc/paper/2020/hash/eccd2a86bae4728b38627162ba297828-Abstract.html
  • [IJCAI20a] Joao Marques-Silva, Carlos Mencía: Reasoning About Inconsistent Formulas. IJCAI 2020: 4899-4906 Paper: https://doi.org/10.24963/ijcai.2020/682
  • [CP20a] Alexey Ignatiev, Martin C. Cooper, Mohamed Siala, Emmanuel Hebrard, Joao Marques-Silva: Towards Formal Fairness in Machine Learning. CP 2020: 846-867 Paper: https://doi.org/10.1007/978-3-030-58475-7_49
  • [ECAI20] Oleg Zaikin, Alexey Ignatiev, João Marques-Silva: Branch Location Problems with Maximum Satisfiability. ECAI 2020: 379-386. Paper: https://doi.org/10.3233/FAIA200116
  • [SAT20] Carlos Mencía, Joao Marques-Silva: Reasoning About Strong Inconsistency in ASP. SAT 2020: 332-342. Paper: https://doi.org/10.1007/978-3-030-51825-7_24
  • [AIxIA20] Alexey Ignatiev, Nina Narodytska, Nicholas Asher, Joao Marques-Silva: From Contrastive to Abductive Explanations and Back Again. AI*IA 2020: 335-355 Paper: https://doi.org/10.1007/978-3-030-77091-4_21
  • [ORL20] David A. Cohen, Martin C. Cooper, Artem Kaznatcheev, Mark Wallace: Steepest ascent can be exponential in bounded treewidth problems. Oper. Res. Lett. 48(3): 217-224 (2020)
  • [CP20b] Martin C. Cooper: Strengthening Neighbourhood Substitution. CP 2020: 126-142
  • [GKR20] David A. Cohen, Martin C. Cooper, Peter G. Jeavons, Stanislav Zivný: Galois Connections for Patterns: An Algebra of Labelled Graphs. GKR 2020: 125-150
  • [IJCAI20b] Martin C. Cooper, Achref El Mouelhi, Cyril Terrioux: Variable Elimination in Binary CSPs (Extended Abstract). IJCAI 2020: 5035-5039
  • [KR20] Martin C. Cooper, Andreas Herzig, Frédéric Maris, Elise Perrotin, Julien Vianey: Lightweight Parallel Multi-Agent Epistemic Planning. KR 2020: 274-283
  • [STACS20] Martin C. Cooper, Simon de Givry, Thomas Schiex: Graphical Models: Queries, Complexity, Algorithms (Tutorial). STACS 2020: 4:1-4:22
  • [IJCAI20c] Hao Hu, Mohamed Siala, Emmanuel Hebrard and Marie-José Huguet: Learning Optimal Decision Trees with MaxSAT and its Integration in AdaBoost. IJCAI 2020: 1170-1176 Paper: https://doi.org/10.24963/ijcai.2020/163
  • [CP20c] Valentin Antuori, Emmanuel Hebrard, Marie-José Huguet, Siham Essodaigui and Alain Nguyen: Leveraging Reinforcement Learning, Constraint Programming and Local Search: A Case Study in Car Manufacturing. CP 2020: 657-672
  • [AAAI20] Arthur Godet, Xavier Lorca, Emmanuel Hebrard and Gilles Simonin: Using Approximation within Constraint Programming to Solve the Parallel Machine Scheduling Problem with Additional Unit Resources. IJCAI 2020: 1170-1176 Paper: https://doi.org/10.1609/aaai.v34i02.5510
  • [JAIR20] Emmanuel Hebrard and George Katsirelos. Constraint and Satisfiability Reasoning for Graph Coloring. JAIR 2020: 33-65

[2019] 3 A*, 4 A , 2 B

  • [NIPS19] Alexey Ignatiev, Nina Narodytska, Joao Marques-Silva: On Relating Explanations and Adversarial Examples. NeurIPS 2019: 15857-15867 Paper: https://proceedings.neurips.cc/paper/2019/hash/7392ea4ca76ad2fb4c9c3b6a5c6e31e3-Abstract.html
  • [AAAI19] Alexey Ignatiev, Nina Narodytska, João Marques-Silva: Abduction-Based Explanations for Machine Learning Models. AAAI 2019: 1511-1519 Paper: https://doi.org/10.1609/aaai.v33i01.33011511
  • [IJCAI19] Alexey Ignatiev, António Morgado, Georg Weissenbacher, Joao Marques-Silva: Model- Based Diagnosis with Multiple Observations. IJCAI 2019: 1108-1115.Paper: https://doi.org/10.24963/ijcai.2019/155
  • [SAT19a] Nina Narodytska, Aditya A. Shrotri, Kuldeep S. Meel, Alexey Ignatiev, Joao Marques-Silva: Assessing Heuristic Machine Learning Explanations with Model Counting. SAT 2019: 267-278 Paper: https://doi.org/10.1007/978-3-030-24258-9_19
  • [SAT19b] Carlos Mencía, Oliver Kullmann, Alexey Ignatiev, Joao Marques-Silva: On Computing the Union of MUSes. SAT 2019: 211-221. Paper: https://doi.org/10.1007/978-3-030-24258-9_15 [SAT19c] António Morgado, Alexey Ignatiev, Maria Luisa Bonet, Joao Marques-Silva, Sam Buss: DRMaxSAT with MaxHS: First Contact. SAT 2019: 239-249 Paper: https://doi.org/10.1007/978-3-030- 24258-9_17
  • [CPAIOR19a] Emmanuel Hebrard and George Katsirelos: A Hybrid Approach for Exact Coloring of Massive Graphs. CPAIOR 2019: 374-390
  • [CPAIOR19b] Begum Genc, Mohamed Siala, Gilles Simonin and Barry O’Sullivan: An Approach to Robustness in the Stable Roommates Problem and Its Comparison with the Stable Marriage Problem.CPAIOR 2019: 320-336
  • [TCS19] Begum Genc, Mohamed Siala, Gilles Simonin and Barry O’Sullivan: Complexity Study for the Robust Stable Marriage Problem. Theor. Comput. Sci. 2019: 76-92
En savoir +

Joao Marques Silva, l’IA en toute logique.

Le chercheur portugais Joao Marques Silva a posé ses valises dans la ville rose il y a deux ans. Il y poursuit ses recherches pour expliquer les décisions prises par les algorithmes. Avec l’aide de raisonnements logiques, il cherche à vérifier les modèles d’apprentissage automatique. Portrait d’un globe-trotter de l’intelligence artificielle (IA).

Lire l’article Exploreur

Ne manquez rien !

Inscrivez-vous pour recevoir l'actualité d'ANITI chaque mois.

Nous n’envoyons pas de messages indésirables !

fr_FRFrench
fr_FRFrench en_GBEnglish