Section: Partnerships and Cooperations

International Initiatives

Inria International Partners

  • Inria International partnership with Leoben, Austria; starting October 2014; duration: 4 years.

    • Ronald Ortner and Peter Auer: Montanuniversität Leoben (Austria).

    • Reinforcement learning (RL) deals with the problem of interacting with an unknown stochastic environment that occasionally provides rewards, with the goal of maximizing the cumulative reward. The problem is well-understood when the unknown environment is a finite-state Markov process. This collaboration is centered around reducing the general RL problem to this case.

      In particular, the following problems are considered: representation learning, learning in continuous-state environments, bandit problems with dependent arms, and pure exploration in bandit problems. On each of these problems we have successfully collaborated in the past, and plan to sustain this collaboration possibly extending its scopes.

Informal International Partners
  • Technion - Israel Institute of Technology, Haifa, Israel.

    • Odalric-Ambrym Maillard Collaborator

      Daniil Ryabko has worked with Odalric Maillard on representation learning for reinforcement learning problems. It led to a paper in AISTATS [46] .

  • School of Computer Science, Carnegie Mellon University, USA.

    • Prof. Emma Brunskill Collaborator

    • Mohammad Gheshlaghi Azar, (now at Northwestern University in Chicago) Collaborator

      A. Lazaric continued his collaboration on transfer in multi-arm bandit and reinforcement learning which led to one publication at ICML'14. We have submitted an associate team project with E. Brunskill on the topic of multi-arm bandit applied to education.

  • Technicolor Research, Palo Alto.

    • Branislav Kveton Collaborator

      Michal Valko and Rémi Munos worked with Branislav on Spectral Bandits aimed at recommendation for the entertainment content recommendation. Michal continued the ongoing research on online semi-supervised learning and this year delivered the algorithm for a challenging single picture per person setting. Victor Gabillon has spent 6 month at Technicolor as an intern to work on the sequential learning with submodularity, which resulted in 1 accepted paper at NIPS, 1 in ICML, and 1 in AAAI.

  • University of Cambridge (UK)

    • Alexandra Carpentier Collaborator

    • Michal Valko collaborates with A. Carpentier on extreme event detection (such as network intrusion) with limited allocation capabilities.

  • Politecnico di Milano (Italy)

    • Prof. Marcello Restelli and Prof. Nicola Gatti Collaborators

    • A. Lazaric continued his collaboration on transfer in reinforcement learning which leads to a publication in NIPS'14. Furthermore, we have submitted a journal version of an application of multi-arm bandit in sponsored search auctions which is currently under review.