29 citations · 78 across the 12 of their papers we have counts for
7 papers · 1 filter
Data-Efficient Scaling-Law Discovery for Recommendation Systems via Coupled Hyperparameter Scaling
John Martabano Landy, Louis C. Tiao, Yao Xuan +10
Large-scale ranking and recommendation models of Web platforms benefit from increased compute much as large language models do, and their scaling behavior is broadly power-law in f…
Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch
Paul Brunzema, Louis Tiao, Nhat Le +3
Bayesian optimization (BO) has become the standard tool for sample-efficient optimization and owes its efficiency to uncertainty-aware search driven by generic statistical priors.…
Learning Concave Bid Shading Strategies in Online Auctions via Measure-valued Proximal Optimization
Iman Nodozi, Djordje Gligorijevic, Abhishek Halder
This work proposes a bid shading strategy for first-price auctions as a measure-valued optimization problem. We consider a standard parametric form for bid shading and formulate th…
Time-Aware Prospective Modeling of Users for Online Display Advertising
Djordje Gligorijevic, Jelena Gligorijevic, Aaron Flores
Prospective display advertising poses a great challenge for large advertising platforms as the strongest predictive signals of users are not eligible to be used in the conversion p…
Improving confidence while predicting trends in temporal disease networks
Djordje Gligorijevic, Jelena Stojanovic, Zoran Obradovic
For highly sensitive real-world predictive analytic applications such as healthcare and medicine, having good prediction accuracy alone is often not enough. These kinds of applicat…
Modeling Customer Engagement from Partial Observations
Jelena Stojanovic, Djordje Gligorijevic, Zoran Obradovic
It is of high interest for a company to identify customers expected to bring the largest profit in the upcoming period. Knowing as much as possible about each customer is crucial f…
Semi-supervised learning for structured regression on partially observed attributed graphs
Jelena Stojanovic, Milos Jovanovic, Djordje Gligorijevic +1
Conditional probabilistic graphical models provide a powerful framework for structured regression in spatio-temporal datasets with complex correlation patterns. However, in real-li…