Criteo is organizing a competition of machine learning on aggregated, differentially private data in conjunction with the AdKDD'21 workshop. We thought it could be of interest to you and to the community of researchers and practitioners interested in machine learning and privacy.
In two words, the tasks are to learn click and sales prediction models that operate on aggregated, noisy data. We believe that the aggregation (features + labels), the noise level, and the high cardinality of features present novel, unique challenges. The competition will last until July 31st and the top 3 winners of each task will share $20,000 of prize money and be invited to present their solution to the workshop at KDD'21. Important information: * Workshop website: https://www.adkdd.org/ * Competition website: https://competitions.codalab.org/competitions/31485 * Contact address: adkdd21challe...@googlegroups.com<mailto:adkdd21challe...@googlegroups.com> Data and evaluation code will be open-sourced at the end of the challenge to permit publication of original solutions in relevant research venues. Eustache Diemert, for the challenge organization team at Criteo
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