Evgeny Frolov

According to our database, Evgeny Frolov authored at least 20 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Federated privacy-preserving collaborative filtering for on-device next app prediction.

Albert Saiapin, Gleb Balitskiy, Daniel Bershatsky, Aleksandr Katrutsa, Evgeny Frolov, Alexey A. Frolov, Ivan V. Oseledets, Vitaliy Kharin

User Model. User Adapt. Interact., September, 2024

Cross-Domain Latent Factors Sharing via Implicit Matrix Factorization.

Abdulaziz Samra, Evgeny Frolov, Alexey Vasilev, Alexander Grigorievskiy, Anton Vakhrushev

CoRR, 2024

End-to-End Graph-Sequential Representation Learning for Accurate Recommendations.

Vladimir Baikalov, Evgeny Frolov

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Cross-Domain Latent Factors Sharing via Implicit Matrix Factorization.

Abdulaziz Samra, Evgeny Frolov, Alexey Vasilev, Alexander Grigorevskiy, Anton Vakhrushev

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs.

Gleb Mezentsev, Danil Gusak, Ivan V. Oseledets, Evgeny Frolov

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Self-Attentive Sequential Recommendations with Hyperbolic Representations.

Evgeny Frolov, Tatyana Matveeva, Leyla Mirvakhabova, Ivan V. Oseledets

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential Recommenders.

Danil Gusak, Gleb Mezentsev, Ivan V. Oseledets, Evgeny Frolov

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Dynamic Collaborative Filtering for Matrix- and Tensor-based Recommender Systems.

Albert Saiapin, Ivan V. Oseledets, Evgeny Frolov

CoRR, 2023

Mitigating Human and Computer Opinion Fraud via Contrastive Learning.

Yuliya Tukmacheva, Ivan V. Oseledets, Evgeny Frolov

CoRR, 2023

Tensor-Based Sequential Learning via Hankel Matrix Representation for Next Item Recommendations.

Evgeny Frolov, Ivan V. Oseledets

IEEE Access, 2023

2022

Tensor-based Collaborative Filtering With Smooth Ratings Scale.

Nikita Marin, Elizaveta Makhneva, Maria Lysyuk, Vladimir Chernyy, Ivan V. Oseledets, Evgeny Frolov

CoRR, 2022

Are Quantum Computers Practical Yet? A Case for Feature Selection in Recommender Systems using Tensor Networks.

Artyom Nikitin, Andrei Chertkov, Rafael Ballester-Ripoll, Ivan V. Oseledets, Evgeny Frolov

CoRR, 2022

MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering.

Viktoria Chekalina, Anton Razzhigaev, Albert Sayapin, Evgeny Frolov, Alexander Panchenko

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 2022

2021

Dynamic Modeling of User Preferences for Stable Recommendations.

Oluwafemi Olaleke, Ivan V. Oseledets, Evgeny Frolov

Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, 2021

2020

Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks.

Leyla Mirvakhabova, Evgeny Frolov, Valentin Khrulkov, Ivan V. Oseledets, Alexander Tuzhilin

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

2019

HybridSVD: when collaborative information is not enough.

Evgeny Frolov, Ivan V. Oseledets

Proceedings of the 13th ACM Conference on Recommender Systems, 2019

2018

Revealing the Unobserved by Linking Collaborative Behavior and Side Knowledge.

Evgeny Frolov, Ivan V. Oseledets

CoRR, 2018

Matrix Factorization for Collaborative Recommendations.

Evgeny Frolov, Ivan V. Oseledets

Proceedings of the Collaborative Recommendations, 2018

2017

Tensor methods and recommender systems.

Evgeny Frolov, Ivan V. Oseledets

WIREs Data Mining Knowl. Discov., 2017

2016

Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks.

Evgeny Frolov, Ivan V. Oseledets

Proceedings of the 10th ACM Conference on Recommender Systems, 2016