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Learning and Optimization (A&O)

Group Members
  Group leader
    SEBAG Michèle

  Faculty
    CAILLOU Philippe
    CHARPIAT Guillaume
    DECELLE Aurélien
    DOAN Bich-Liên
    FURTLEHNER Cyril
    GERMAIN Cécile
    GUYON Isabelle
    JEANNOT Maëva
    LANDES François
    SCHOENAUER Marc
    SEBAG Michèle
    SPYRATOS Nicolas
    TUBARO Paola

  Non-permanent research staff
    ALFONSO NAYA Victor
    ATIENZA Nicolas
    BARTENLIAN Eléonore
    BIED Guillaume
    BUI Olivier
    CARRION OJEDA Dustin
    DONG Shuyu
    FELARDOS Loris
    FERREIRA LEITE Alessandro
    Goutierre Emmanuel
    HU Jiahui
    JALAL Reda
    JOULIN Mandie
    LACOMBE Armand
    LAUZZANA Gabriel
    LIU Wenzhuo
    MENIER Emmanuel
    MUSSARD Romain
    NASTORG Matthieu
    NATHAN Solal
    PAVAO Adrien
    PEZZICOLI Francesco
    POINSOT Audrey
    RAIMAN Jonathan
    SCHIMMENTI Vincenzo Maria
    SCHWENCKE Nilo
    SERRE Gaëtan
    SUN Haozhe
    TORRES CIERPE Juana
    TRAN Dinh Tuan
    TREGUER Sébastien
    VASQUEZ LEIVA Francisco
    VERBOCKHAVEN Manon
    WIRTH Assia
    YAN Shiyang

  Visitors
    GOZUKAN Hande
    MEYER Lucas

Research activities
  Numerical stochastic optimization
  Algorithm control and hyper-parameter tuning
  Optimal decision making under uncertainty
  New criteria design
  Large scale modelling

Joint Inria project teams
  TAO

Software & patents
  Django: theta-subsumption test for Relational Learning
  GUIDE: A Graphical User Interface for EA C++ library developpment
  Mash-WP6: A stochastic dynamic programming framework
  Contributions to the GNU Scientific Library: Contributions to the GNU Scientific Library
  SIMBAD: Simbad, A mobile robot simulator for Autonomous and Evolutionary Robotics
  Contribution to Scilab: Contribution to Scilab
  MoGo: Computer-Go program
  CMA-ES: Covariance Matrix Evolution Strategy
  COCO: Comparing Continuous Optimizers
  GridObservatory: Grid Observatory
  cTuning: public repository and tools for collaborative and statistical program and architecture characterization and optimization
  MultiBoost: MultiBoost
  Metis: Metis
  ACM-ES: Surrogate models for CMA-ES
  Codalab: Codalab
  CARTOLABE: CARTOLABE
  io.datascience: io.datascience
  DNADNA: Deep Neural Architectures for DNA

Recent Ph.D. dissertations & faculty habilitations
  Generative modeling: statistical physics of Restricted Boltzmann Machines, learning with missing information and scalable training of Linear Flows
  Verification and validation of Machine Learning techniques
  Deep latent variable models: from properties to structures

Seminars
Heterogeneous Treatment Effects Estimation: When Machine Learning meets multiple treatments regime
Naoufal Acharki
2 June 2022 10h30


TUTORIAL CODALAB - Apprenez à organiser un challenge
Adrien Pavao
13 April 2022 00h00


Generative Neural Networks for Observational Causal Discovery
Diviyan Kalainathan
7 April 2022 10h30


Organiser des challenges avec la plateforme Codalab
Isabelle Guyon, Anne-Catherine Letournel, Tuan Tran, Adrien Pavao
6 April 2022 14h30


atelier slurm 'utilisateurs'
Diviyan et Corentin
18 February 2019 13h30


Atelier slurm 'administrateurs'
Diviyan et Corentin
10 December 2018 13h30


Causal Network Inference for Biology Workshop - Amphi Dig. Shannon
H. Isambert, O Goudet, L. Paulevé
27 February 2017 09h45


From Stochastic Search to Programming by Optimisation: My Quest for Automating the Design of High-Performance Algorithms
Holger H. Hoos
14 October 2014 14h30


Collective Mind Framework: systematizing and crowdsourcing multi-objective auto-tuning
Grigori Fursin
17 December 2013 14h30


Continuous MCTS for hydroelectric scheduling
Adrien Couëtoux
16 July 2013 14h30


Operator-valued kernel-based models for biological network inference
Florence d’Alché-Buc
4 June 2013 14h30


Sorting and Ranking: Two Unrelated Talks
Marco Bressan
23 April 2013 14h00


From Artificial Evolution to Computational Evolution
Wolfgang Banzhaf
25 February 2010 14h30


Partially Observable Markov Decision Processes : An overview
Alain Dutech
26 January 2010 14h30


Elementary Landscapes: On the semi-decomposibility of select NP-hard optimization problems
Darrell Whitley
15 September 2009 14h30


Kernel-based Methods for Detection
Zaid Harchaoui
24 March 2009 14h30


Résultats majeurs
MoGo: A program playing Go
1 August 2006
A program playing Go:
Winner of several International competition since 2006
Contributors:
Yizao Wang, Sylvain Gelly, Rémi Munos, Olivier Teytaud, Pierre-Arnaud Coquelin.

Software & patents