2 citations · 2 across the 4 of their papers we have counts for
4 papers
A Bag of Tricks for Scaling CPU-based Deep FFMs to more than 300m Predictions per Second
Blaž Škrlj, Benjamin Ben-Shalom, Grega Gašperšič +5
Field-aware Factorization Machines (FFMs) have emerged as a powerful model for click-through rate prediction, particularly excelling in capturing complex feature interactions. In t…
Drifter: Efficient Online Feature Monitoring for Improved Data Integrity in Large-Scale Recommendation Systems
Blaž Škrlj, Nir Ki-Tov, Lee Edelist +5
Real-world production systems often grapple with maintaining data quality in large-scale, dynamic streams. We introduce Drifter, an efficient and lightweight system for online feat…
Unleash the Power of Context: Enhancing Large-Scale Recommender Systems with Context-Based Prediction Models
Jan Hartman, Assaf Klein, Davorin Kopič +1
In this work, we introduce the notion of Context-Based Prediction Models. A Context-Based Prediction Model determines the probability of a user's action (such as a click or a conve…
Exploration with Model Uncertainty at Extreme Scale in Real-Time Bidding
Jan Hartman, Davorin Kopič
In this work, we present a scalable and efficient system for exploring the supply landscape in real-time bidding. The system directs exploration based on the predictive uncertainty…