Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks. - Evgeny Frolov; Ivan V. Oseledets (RecSys, 2016)

Tensor methods and recommender systems. - Evgeny Frolov; Ivan V. Oseledets (WIREs Data Mining Knowl. Discov., 2017)

Matrix Factorization for Collaborative Recommendations. - Evgeny Frolov; Ivan V. Oseledets (Collaborative Recommendations, 2018)

Revealing the Unobserved by Linking Collaborative Behavior and Side Knowledge. - Evgeny Frolov; Ivan V. Oseledets (CoRR, 2018)

HybridSVD: when collaborative information is not enough. - Evgeny Frolov; Ivan V. Oseledets (RecSys, 2019)

Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks. - Leyla Mirvakhabova; Evgeny Frolov; Valentin Khrulkov; Ivan V. Oseledets; Alexander Tuzhilin (RecSys, 2020)

Dynamic Modeling of User Preferences for Stable Recommendations. - Oluwafemi Olaleke; Ivan V. Oseledets; Evgeny Frolov (UMAP, 2021)

MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering. - Viktoria Chekalina; Anton Razzhigaev; Albert Sayapin; Evgeny Frolov; Alexander Panchenko (ACL (student), 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)

Tensor-based Collaborative Filtering With Smooth Ratings Scale. - Nikita Marin; Elizaveta Makhneva; Maria Lysyuk; Vladimir Chernyy; Ivan V. Oseledets; Evgeny Frolov (CoRR, 2022)

Tensor-Based Sequential Learning via Hankel Matrix Representation for Next Item Recommendations. - Evgeny Frolov; Ivan V. Oseledets (IEEE Access, 2023)

Mitigating Human and Computer Opinion Fraud via Contrastive Learning. - Yuliya Tukmacheva; Ivan V. Oseledets; Evgeny Frolov (CoRR, 2023)

Dynamic Collaborative Filtering for Matrix- and Tensor-based Recommender Systems. - Albert Saiapin; Ivan V. Oseledets; Evgeny Frolov (CoRR, 2023)

RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential Recommenders. - Danil Gusak; Gleb Mezentsev; Ivan V. Oseledets; Evgeny Frolov (CIKM, 2024)

Self-Attentive Sequential Recommendations with Hyperbolic Representations. - Evgeny Frolov; Tatyana Matveeva; Leyla Mirvakhabova; Ivan V. Oseledets (RecSys, 2024)

Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs. - Gleb Mezentsev; Danil Gusak; Ivan V. Oseledets; Evgeny Frolov (RecSys, 2024)

Cross-Domain Latent Factors Sharing via Implicit Matrix Factorization. - Abdulaziz Samra; Evgeny Frolov; Alexey Vasilev; Alexander Grigorevskiy; Anton Vakhrushev (RecSys, 2024)

End-to-End Graph-Sequential Representation Learning for Accurate Recommendations. - Vladimir Baikalov; Evgeny Frolov (WWW (Companion Volume), 2024)

Cross-Domain Latent Factors Sharing via Implicit Matrix Factorization. - Abdulaziz Samra; Evgeny Frolov; Alexey Vasilev; Alexander Grigorievskiy; Anton Vakhrushev (CoRR, 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., 2024)

Knowledge Graph Completion with Mixed Geometry Tensor Factorization. - Viacheslav Yusupov; Maxim Rakhuba; Evgeny Frolov (AISTATS, 2025)

Generalized Fisher-Weighted SVD: Scalable Kronecker-Factored Fisher Approximation for Compressing Large Language Models. - Viktoriia Chekalina; Daniil Moskovskiy; Daria Cherniuk; Maxim Kurkin; Andrey Kuznetsov; Evgeny Frolov (CoRR, 2025)

Time to Split: Exploring Data Splitting Strategies for Offline Evaluation of Sequential Recommenders. - Danil Gusak; Anna Volodkevich; Anton Klenitskiy; Alexey Vasilev; Evgeny Frolov (CoRR, 2025)

Matrix-Free Two-to-Infinity and One-to-Two Norms Estimation. - Askar Tsyganov; Evgeny Frolov; Sergey Samsonov; Maxim Rakhuba (CoRR, 2025)

Maximum Impact with Fewer Features: Efficient Feature Selection for Cold-Start Recommenders through Collaborative Importance Weighting. - Nikita Sukhorukov; Danil Gusak; Evgeny Frolov (CoRR, 2025)

Recommendation Is a Dish Better Served Warm. - Danil Gusak; Nikita Sukhorukov; Evgeny Frolov (CoRR, 2025)

Leveraging Geometric Insights in Hyperbolic Triplet Loss for Improved Recommendations. - Viacheslav Yusupov; Maxim Rakhuba; Evgeny Frolov (CoRR, 2025)

Benefiting from Negative yet Informative Feedback by Contrasting Opposing Sequential Patterns. - Veronika Ivanova; Evgeny Frolov; Alexey Vasilev (CoRR, 2025)