Scaling TensorFlow to 300 million predictions per second. - Jan Hartman; Davorin Kopic (RecSys, 2021)

Exploration with Model Uncertainty at Extreme Scale in Real-Time Bidding. - Jan Hartman; Davorin Kopic (RecSys, 2022)

Dynamic Surrogate Switching: Sample-Efficient Search for Factorization Machine Configurations in Online Recommendations. - Blaz Skrlj; Adi Schwartz; Jure Ferlez; Davorin Kopic; Naama Ziporin (RecSys, 2022)

Feature embedding in click-through rate prediction. - Samo Pahor; Davorin Kopic; Jure Demsar (CoRR, 2022)

Drifter: Efficient Online Feature Monitoring for Improved Data Integrity in Large-Scale Recommendation Systems. - Blaz Skrlj; Nir Ki-Tov; Lee Edelist; Natalia Silberstein; Hila Weisman-Zohar; Blaz Mramor; Davorin Kopic; Naama Ziporin (ORSUM@RecSys, 2023)

Unleash the Power of Context: Enhancing Large-Scale Recommender Systems with Context-Based Prediction Models. - Jan Hartman; Assaf Klein; Davorin Kopic; Natalia Silberstein (RecSys, 2023)

A Bag of Tricks for Scaling CPU-based Deep FFMs to more than 300m Predictions per Second. - Blaz Skrlj; Benjamin Ben-Shalom; Grega Gaspersic; Adi Schwartz; Ramzi Hoseisi; Naama Ziporin; Davorin Kopic; Andraz Tori (AdKDD@KDD, 2024)