8 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…
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…
BAT: Benchmark for Auto-bidding Task
Alexandra Khirianova, Ekaterina Solodneva, Andrey Pudovikov +5
The optimization of bidding strategies for online advertising slot auctions presents a critical challenge across numerous digital marketplaces. A significant obstacle to the develo…
RARe: Raising Ad Revenue Framework with Context-Aware Reranking
Ekaterina Solodneva, Alexandra Khirianova, Aleksandr Katrutsa +4
Modern recommender systems excel at optimizing search result relevance for e-commerce platforms. While maintaining this relevance, platforms seek opportunities to maximize revenue…