3 citations · 8 across the 5 of their papers we have counts for
5 papers
AI-assisted Coding with Cody: Lessons from Context Retrieval and Evaluation for Code Recommendations
Jan Hartman, Rishabh Mehrotra, Hitesh Sagtani +5
In this work, we discuss a recently popular type of recommender system: an LLM-based coding assistant. Connecting the task of providing code recommendations in multiple formats to…
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…
Predicting the Popularity of Games on Steam
Andraž De Luisa, Jan Hartman, David Nabergoj +5
The video game industry has seen rapid growth over the last decade. Thousands of video games are released and played by millions of people every year, creating a large community of…
Scaling TensorFlow to 300 million predictions per second
Jan Hartman, Davorin Kopič
We present the process of transitioning machine learning models to the TensorFlow framework at a large scale in an online advertising ecosystem. In this talk we address the key cha…