4 papers
Optimizing Online Advertising with Multi-Armed Bandits: Mitigating the Cold Start Problem under Auction Dynamics
Anastasiia Soboleva, Andrey Pudovikov, Roman Snetkov +3
Online advertising platforms often face a common challenge: the cold start problem. Insufficient behavioral data (clicks) makes accurate click-through rate (CTR) forecasting of new…
Optimal Traffic Allocation for Multi-Slot Sponsored Search: Balance of Efficiency and Fairness
Anastasiia Soboleva, Alexander Ledovsky, Yuriy Dorn +3
The majority of online marketplaces offer promotion programs to sellers to acquire additional customers for their products. These programs typically allow sellers to allocate adver…
On quasi-convex smooth optimization problems by a comparison oracle
A. V. Gasnikov, M. S. Alkousa, A. V. Lobanov +4
Frequently, when dealing with many machine learning models, optimization problems appear to be challenging due to a limited understanding of the constructions and characterizations…
Fast UCB-type algorithms for stochastic bandits with heavy and super heavy symmetric noise
Yuriy Dorn, Aleksandr Katrutsa, Ilgam Latypov +1
In this study, we propose a new method for constructing UCB-type algorithms for stochastic multi-armed bandits based on general convex optimization methods with an inexact oracle.…