9 papers @ICML 2020, from Criteo AI Lab

By: Criteo AI Lab / 01 Jun 2020

We are happy to have 9 papers co-authored by members of the Criteo AI Lab getting in ICML 2020:

  1. Gradient-free Online Learning in Continuous Games with Delayed Rewards,  A. Héliou, P. Mertikopoulos, and Z. Zhou.
  2. Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games, T. Lin, Z. Zhou, P. Mertikopoulos, and M. Jordan. https://arxiv.org/abs/2002.09806
  3. A New Regret Analysis for Adam-type Algorithms, A. Alacaoglu, Y. Malitsky, P. Mertikopoulos, and V. Cevher. https://arxiv.org/abs/2003.09729
  4. Partial Trace Regression and Low-Rank Kraus Decomposition, H. Kadri, S. Ayache, R. Huusari, A. Rakotomamonjy, L. Ralaivola
  5. Improved Optimistic Algorithms for Logistic Bandits, L. Faury, M. Abeille, C. Calauzènes, and O. Fercoq. https://arxiv.org/abs/2002.07530
  6. Real-Time Optimization for Online Learning in Auctions, L. Croissant, M. Abeille, C. Calauzènes
  7. Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation, M. Abeille and Alessandro Lazaric
  8. Learning disconnected manifolds: a no GAN’s land, U. Tanielian, T. Issenhuth, E. Dohmatob, J. Mary
  9. Stochastic Latent Residual Video Prediction, J.-Y. Franceschi, E. Delasalles, M. Chen, S. Lamprier, P. Gallinari. https://arxiv.org/pdf/2002.09219