Tensor methods and recommender systems E Frolov, I Oseledets Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 7 (3 …, 2017 | 157 | 2017 |
HybridSVD: when collaborative information is not enough E Frolov, I Oseledets Proceedings of the 13th ACM conference on recommender systems, 331-339, 2019 | 33 | 2019 |
Performance of hyperbolic geometry models on top-n recommendation tasks L Mirvakhabova, E Frolov, V Khrulkov, I Oseledets, A Tuzhilin Proceedings of the 14th ACM Conference on Recommender Systems, 527-532, 2020 | 31 | 2020 |
Fifty shades of ratings: how to benefit from a negative feedback in top-N recommendations tasks E Frolov, I Oseledets Proceedings of the 10th ACM Conference on Recommender Systems, 91-98, 2016 | 28 | 2016 |
MEKER: memory efficient knowledge embedding representation for link prediction and question answering V Chekalina, A Razzhigaev, A Sayapin, E Frolov, A Panchenko arXiv preprint arXiv:2204.10629, 2022 | 11 | 2022 |
Dynamic modeling of user preferences for stable recommendations O Olaleke, I Oseledets, E Frolov Proceedings of the 29th ACM Conference on User Modeling, Adaptation and …, 2021 | 8 | 2021 |
Are quantum computers practical yet? A case for feature selection in recommender systems using tensor networks A Nikitin, A Chertkov, R Ballester-Ripoll, I Oseledets, E Frolov arXiv preprint arXiv:2205.04490, 2022 | 7 | 2022 |
Tensor-based sequential learning via Hankel matrix representation for next item recommendations E Frolov, I Oseledets IEEE Access 11, 6357-6371, 2023 | 6 | 2023 |
Tensor-based collaborative filtering with smooth ratings scale N Marin, E Makhneva, M Lysyuk, V Chernyy, I Oseledets, E Frolov arXiv preprint arXiv:2205.05070, 2022 | 4 | 2022 |
RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential Recommenders D Gusak, G Mezentsev, I Oseledets, E Frolov arXiv preprint arXiv:2408.02354, 2024 | 1 | 2024 |
Revealing the Unobserved by Linking Collaborative Behavior and Side Knowledge E Frolov, I Oseledets arXiv preprint arXiv:1807.10634, 2018 | 1 | 2018 |
Low Rank Models for Recommender Systems with Limited Preference Information E Frolov Skolkovo Institute of Science and Technology, 2018 | 1 | 2018 |
Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs G Mezentsev, D Gusak, I Oseledets, E Frolov arXiv preprint arXiv:2409.18721, 2024 | | 2024 |
End-to-End Graph-Sequential Representation Learning for Accurate Recommendations V Baikalov, E Frolov Companion Proceedings of the ACM on Web Conference 2024, 501-504, 2024 | | 2024 |
Federated privacy-preserving collaborative filtering for on-device next app prediction A Saiapin, G Balitskiy, D Bershatsky, A Katrutsa, E Frolov, A Frolov, ... User Modeling and User-Adapted Interaction, 1-30, 2024 | | 2024 |
Dynamic Collaborative Filtering for Matrix-and Tensor-based Recommender Systems A Saiapin, I Oseledets, E Frolov arXiv preprint arXiv:2312.10064, 2023 | | 2023 |
Mitigating Human and Computer Opinion Fraud via Contrastive Learning Y Tukmacheva, I Oseledets, E Frolov arXiv preprint arXiv:2301.03025, 2023 | | 2023 |
Matrix factorization for collaborative recommendations E Frolov, I Oseledets Collaborative Recommendations: Algorithms, Practical Challenges and …, 2019 | | 2019 |
Hyperbolic Embeddings in Sequential Self-Attention for Improved Next-Item Recommendations E Frolov, L Bashaeva, L Mirvakhabova, I Oseledets | | |
HDI Lab research projects 2023/24 A Goldman, E Frolov, E Kosov, E Lagutin, I Levin, F Noskov, N Puchkin, ... | | |