Google’s mission presents many exciting algorithmic and optimization challenges across different product areas including Search, Ads, Social, and Google Infrastructure. These include optimizing internal systems such as scheduling the machines that power the numerous computations done each day, as well as optimizations that affect core products and users, from online allocation of ads to page-views to automatic management of ad campaigns, and from clustering large-scale graphs to finding best paths in transportation networks. Other than employing new algorithmic ideas to impact millions of users, Google researchers contribute to the state-of-the-art research in these areas by publishing in top conferences and journals.
Recent publications
Efficient List-Decodable Regression using Batches
Efficient List-Decodable Regression using Batches, ICML (2023)
Nash Equilibria of The Multiplayer Colonel Blotto Game on the Interval and Arbitrary Measure Spaces
Web And Internet Economics (WINE 2023) (2023) (to appear)
Near Optimal Heteroscedastic Regression with Symbiotic Learning
Conference on Learning Theory (COLT) (2023)
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