10 papers
Fast and Feasible: Permutation-based Constrained Reranking for Revenue Maximization
Svetlana Shirokovskikh, Anastasiia Soboleva, Ekaterina Solodneva +3
Search and recommender systems have produced highly relevant search results. A natural next step in the development of such systems in e-commerce is to rerank these results to incr…
Uncertainty Quantification of Click and Conversion Estimates for the Autobidding
Ivan Zhigalskii, Andrey Pudovikov, Aleksandr Katrutsa +1
Modern e-commerce platforms employ various auction mechanisms to allocate paid slots for a given item. To scale this approach to the millions of auctions, the platforms suggest pro…
Functional multi-armed bandit and the best function identification problems
Yuriy Dorn, Aleksandr Katrutsa, Ilgam Latypov +1
Bandit optimization usually refers to the class of online optimization problems with limited feedback, namely, a decision maker uses only the objective value at the current point t…
Empirical evaluation of the Frank-Wolfe methods for constructing white-box adversarial attacks
Kristina Korotkova, Aleksandr Katrutsa
The construction of adversarial attacks for neural networks appears to be a crucial challenge for their deployment in various services. To estimate the adversarial robustness of a…
Autobidding Arena: unified evaluation of the classical and RL-based autobidding algorithms
Andrey Pudovikov, Alexandra Khirianova, Ekaterina Solodneva +3
Advertisement auctions play a crucial role in revenue generation for e-commerce companies. To make the bidding procedure scalable to thousands of auctions, the automatic bidding (a…
Robust autobidding for noisy conversion prediction models
Andrey Pudovikov, Alexandra Khirianova, Ekaterina Solodneva +4
Managing millions of digital auctions is an essential task for modern advertising auction systems. The main approach to managing digital auctions is an autobidding approach, which…