Criteo AI Lab Blog
20 Jan 2021
5 papers @ICLR 2021, 1 paper @ALT 2021 co-authored by Criteo AI Lab folks!
Happy to have 5 papers accepted at ICLR 2021 (among which 2 oral presentations) and 1 paper at ALT 2021!
- ICLR 2021: Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes (oral), Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel...
01 Oct 2020
9 papers accepted to @NeurIPS20 co-authored by researchers from Criteo AI Lab
We are happy to have 9 papers co-authored by researchers from the Criteo AI Lab at NeurIPS 2020
- Online non-convex optimization with inexact models, A. Héliou, M. Martin, P. Mertikopoulos, and T. Rahier
- Explore aggressively, update conservatively: Stochastic extragradient...
18 Sep 2020
Series of posts on "Counterfactual evaluation and Recommender systems", by A. Gilotte
Alex Gilotte, researcher at the Criteo AI Lab, details how counterfactual reasoning may be applied to evaluate a recommender system.
The first posts introduce the topic and the intuitions behind the mathematics of counterfactual reasoning, and the later...
08 Sep 2020
New post by O. Koch: "The Trade-Offs of Large-Scale Machine Learning: the price of time"
What defines large-scale machine learning? This seemingly innocent question is often answered with petabytes of data and hundreds of GPUs. It turns out that large-scale machine learning does not have much to do with all of that.
02 Sep 2020
Best student ML paper award runner-up @ECMLPKDD
The paper on "A Principle of Least Action for the Training of Neural Networks" by Skander Karkar, Patrick Gallinari and their LIP6_lab co-authors, has been selected as the best student ML paper award Runner-up @ECMLPKDD!
06 Aug 2020
DeepR — Training TensorFlow Models for Production
The Reco team has released DeepR, a package to train deep recommendation models in production! See the full post here, with links to Github, docs, quick start guide and some examples: DeepR on Medium.
03 Jul 2020
One paper accepted at ECCV2020! "Do not mask what you do not need to mask: a parser free Virtual Try-on" Authors: T. Issenhuth (Criteo AI Lab), J. Mary (Criteo AI Lab), C. Calauzènes (Criteo AI Lab)
10 Jun 2020
1 paper accepted at ECML 2020: "A Principle of Least Action for the Training of Neural Networks"
One paper accepted at ECML 2020: A Principle of Least Action for the Training of Neural Networks. Authors. Skander Karkar (LIP6, Sorbonne Université / Criteo AI Lab), Ibrahim Ayed (LIP6, Sorbonne Université), Emmanuel de Bézenac (LIP6, Sorbonne Université)...
01 Jun 2020
9 papers @ICML 2020, from Criteo AI Lab
We are happy to have 9 papers co-authored by members of the Criteo AI Lab getting in ICML 2020:
- Gradient-free Online Learning in Continuous Games with Delayed Rewards, A. Héliou, P. Mertikopoulos, and Z. Zhou.
- Finite-Time Last-Iterate Convergence...
26 May 2020
2 papers accepted @COLT’20, from Criteo AI Lab
Two papers co-authored by Vianney Perchet, researcher at Criteo AI Lab, got accepted at COLT 2020
- Selfish Robustness and Equilibria in Multi-Player Bandits, E. Boursier, V. Perchet. https://arxiv.org/abs/2002.01197
- Covariance-adapting algorithm for semi-bandits with application to sparse rewards, P....