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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…
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…
Best student ML paper award runner-up @ECMLPKDD
The paper on “A Principle of Least Action for the Training of Neural Networks” by…
DeepR — Training TensorFlow Models for Production
The Reco team has released DeepR, a package to train deep recommendation models in production!…
One paper accepted at ECCV2020: “Do not mask what you do not need to mask: a parser free Virtual Try-on”,
One paper accepted at ECCV2020! “Do not mask what you do not need to mask:…
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…
9 papers @ICML 2020, from Criteo AI Lab
We are happy to have 9 papers co-authored by members of the Criteo AI Lab…
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…
2 papers @KDD2020, from Criteo AI Lab
Two papers co-authored by Criteo AI Lab researchers and their colleagues accepted at KDD 2020!…
REVEAL Workshop on “Bandit and Reinforcement Learning from User Interactions”
Our REVEAL workshop about Bandit and RL for user interactions will be held at RecSys’20.…