Nicolas kowalski
Senior Software Engineer, Criteo

Nicolas Kowalski is a senior software engineer at Criteo. His work focuses on developing the platforms and tools that are used by all of Criteo to create any kind of machine learning model, train them, serve them online, and monitor their behavior. Previously, Nicolas earned a PhD in applied mathematics from Paris University Pierre and Marie Curie and spent some time in academia, where he published eight papers in international journals and conferences, including the best paper at the 2012 International Meshing Roundtable.

Sessions

11:00am–11:40am Wednesday, October 30, 2019

Location: Grand Ballroom E

How Criteo optimized and sped up its TensorFlow models by 10x and served them under 5 ms

Applications

Nicolas kowalski (Criteo), Axel Antoniotti (Criteo)

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Criteo's real-time bidding of ad spaces requires its TensorFlow (TF) models to make online predictions in less than 5 ms. Nicolas Kowalski and Axel Antoniotti explain why Criteo moved away from high-level APIs and rewrote its models from scratch, reimplementing cross-features and hashing functions using low-level TF operations in order to factorize as much as possible all TF nodes in its model. Read more.