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Learning and Optimization (A&O)

Group Members
  Group leader
    SEBAG Michèle

    CAILLOU Philippe
    CHARPIAT Guillaume
    DECELLE Aurélien
    FONTANA Laurence
    FRANOVA Marta
    GERMAIN Cécile
    GUYON Isabelle
    SEBAG Michèle
    SPYRATOS Nicolas
    TEYTAUD Olivier
    TUBARO Paola
    VENTOS Véronique

  Non-permanent research staff
    BATU Berna
    BERGER Victor
    BRAME Etienne
    DONNOT Benjamin
    DOQUET Guillaume
    ESTRADE Victor
    FISSORE Giancarlo
    GOUDET Olivier
    JAISWAL Raphaël
    LIU Zhengying
    MAKDOUD Nizam
    MISHRA Sourava Prasad
    NABHAN Marc
    POL Adrian
    RAKOTOARISON Herilalaina
    SANCHEZ Théophile
    SUN Lisheng
    TALLEC Corentin
    TRITAS Aris
    WOLINSKI Pierre

    CHEVALLIER Sylvain
    RAUBY Brice
    TOTH Martin

    BENBOUZID Djalel
    D'ALCHE BUC Florence
    KÉGL Balázs
    PEYRE Rémi

    BARTENLIAN Eléonore
    KHUN Kimang
    PAVAO Adrien
    YANG Mo

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

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

Recent Ph.D. dissertations & faculty habilitations
  Bandits Manchots sur Flux de Données Non Stationnaires
  Uncertainties in Optimization

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
Yizao Wang, Sylvain Gelly, Rémi Munos, Olivier Teytaud, Pierre-Arnaud Coquelin.

Software & patents