More from the Same Authors

• 2022 : Differentially Private Gradient Boosting on Linear Learners for Tabular Data »
  Saeyoung Rho · Shuai Tang · Sergul Aydore · Michael Kearns · Aaron Roth · Yu-Xiang Wang · Steven Wu · Cedric Archambeau
• 2022 Poster: Memory Efficient Continual Learning with Transformers »
  Beyza Ermis · Giovanni Zappella · Martin Wistuba · Aditya Rawal · Cedric Archambeau
• 2022 Poster: Private Synthetic Data for Multitask Learning and Marginal Queries »
  Giuseppe Vietri · Cedric Archambeau · Sergul Aydore · William Brown · Michael Kearns · Aaron Roth · Ankit Siva · Shuai Tang · Steven Wu
• 2020 Session: Orals & Spotlights Track 16: Continual/Meta/Misc Learning »
  Laurent Charlin · Cedric Archambeau
• 2014 Workshop: Learning Semantics »
  Cedric Archambeau · Antoine Bordes · Leon Bottou · Chris J Burges · David Grangier
• 2011 Workshop: Choice Models and Preference Learning »
  Jean-Marc Andreoli · Cedric Archambeau · Guillaume Bouchard · Shengbo Guo · Kristian Kersting · Scott Sanner · Martin Szummer · Paolo Viappiani · Onno Zoeter
• 2011 Session: Spotlight Session 7 »
  Cedric Archambeau
• 2011 Session: Oral Session 9 »
  Cedric Archambeau
• 2011 Poster: Sparse Bayesian Multi-Task Learning »
  Cedric Archambeau · Shengbo Guo · Onno Zoeter
• 2008 Poster: Sparse probabilistic projections »
  Cedric Archambeau · Francis Bach
• 2008 Spotlight: Sparse probabilistic projections »
  Cedric Archambeau · Francis Bach
• 2007 Poster: Variational Inference for Diffusion Processes »
  Cedric Archambeau · Manfred Opper · Yuan Shen · Dan Cornford · John Shawe-Taylor
• 2006 Workshop: Dynamical Systems, Stochastic Processes and Bayesian Inference »
  Manfred Opper · Cedric Archambeau · John Shawe-Taylor