An Incremental Learning framework for Large-scale CTR Prediction

no code implementations • 1 Sep 2022 • Petros Katsileros, Nikiforos Mandilaras, Dimitrios Mallis, Vassilis Pitsikalis, Stavros Theodorakis, Gil Chamiel

In this work we introduce an incremental learning framework for Click-Through-Rate (CTR) prediction and demonstrate its effectiveness for Taboola's massive-scale recommendation service.

Click-Through Rate Prediction Incremental Learning

Deep density networks and uncertainty in recommender systems

no code implementations • ICLR 2018 • Yoel Zeldes, Stavros Theodorakis, Efrat Solodnik, Aviv Rotman, Gil Chamiel, Dan Friedman

Building robust online content recommendation systems requires learning complex interactions between user preferences and content features.

Collaborative Filtering Efficient Exploration +1