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ORCIDEvgeny Frolov
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2020 – today
- 2026
[j4]Viacheslav Yusupov, Nikita Sukhorukov, Evgeny Frolov:
Efficient incorporation of new interactions in graph recommenders via folding-in. User Model. User Adapt. Interact. 36(1): 2 (2026)- 2025
- [c16]Viacheslav Yusupov, Maxim V. Rakhuba, Evgeny Frolov:
Knowledge Graph Completion with Mixed Geometry Tensor Factorization. AISTATS 2025: 4924-4932 - [c15]Viacheslav Yusupov
, Maxim V. Rakhuba, Evgeny Frolov:
Ultra Fast Warm Start Solution for Graph Recommendations. CIKM 2025: 5469-5473 - [c14]Danil Gusak, Anna Volodkevich, Anton Klenitskiy, Alexey Vasilev, Evgeny Frolov:
Time to Split: Exploring Data Splitting Strategies for Offline Evaluation of Sequential Recommenders. RecSys 2025: 874-883 - [c13]Veronika Ivanova, Evgeny Frolov, Alexey Vasilev:
Benefiting from Negative yet Informative Feedback by Contrasting Opposing Sequential Patterns. RecSys 2025: 1142-1147 - [c12]Viacheslav Yusupov, Maxim V. Rakhuba, Evgeny Frolov:
Leveraging Geometric Insights in Hyperbolic Triplet Loss for Improved Recommendations. RecSys 2025: 1217-1221 - [c11]Danil Gusak, Nikita Sukhorukov, Evgeny Frolov:
Recommendation Is a Dish Better Served Warm. RecSys 2025: 1267-1272 - [i30]Viacheslav Yusupov, Maxim V. Rakhuba, Evgeny Frolov:
Knowledge Graph Completion with Mixed Geometry Tensor Factorization. CoRR abs/2504.02589 (2025) - [i29]Viktoriia Chekalina, Daniil Moskovskiy, Daria Cherniuk, Maxim Kurkin, Andrey Kuznetsov, Evgeny Frolov:
Generalized Fisher-Weighted SVD: Scalable Kronecker-Factored Fisher Approximation for Compressing Large Language Models. CoRR abs/2505.17974 (2025) - [i28]Danil Gusak, Anna Volodkevich, Anton Klenitskiy, Alexey Vasilev, Evgeny Frolov:
Time to Split: Exploring Data Splitting Strategies for Offline Evaluation of Sequential Recommenders. CoRR abs/2507.16289 (2025) - [i27]Askar Tsyganov, Evgeny Frolov, Sergey Samsonov, Maxim V. Rakhuba:
Matrix-Free Two-to-Infinity and One-to-Two Norms Estimation. CoRR abs/2508.04444 (2025) - [i26]Nikita Sukhorukov, Danil Gusak, Evgeny Frolov:
Maximum Impact with Fewer Features: Efficient Feature Selection for Cold-Start Recommenders through Collaborative Importance Weighting. CoRR abs/2508.06455 (2025) - [i25]Danil Gusak, Nikita Sukhorukov, Evgeny Frolov:
Recommendation Is a Dish Better Served Warm. CoRR abs/2508.07856 (2025) - [i24]Viacheslav Yusupov, Maxim V. Rakhuba, Evgeny Frolov:
Leveraging Geometric Insights in Hyperbolic Triplet Loss for Improved Recommendations. CoRR abs/2508.11978 (2025) - [i23]Veronika Ivanova, Evgeny Frolov, Alexey Vasilev:
Benefiting from Negative yet Informative Feedback by Contrasting Opposing Sequential Patterns. CoRR abs/2508.14786 (2025) - [i22]Tatyana Matveeva, Aleksandr Katrutsa, Evgeny Frolov:
Dynamic Low-rank Approximation of Full-Matrix Preconditioner for Training Generalized Linear Models. CoRR abs/2508.21106 (2025) - [i21]Viacheslav Yusupov, Maxim V. Rakhuba, Evgeny Frolov:
Ultra Fast Warm Start Solution for Graph Recommendations. CoRR abs/2509.01549 (2025) - [i20]Andrei Chertkov, Artem Basharin, Mikhail Saygin, Evgeny Frolov, Stanislav Straupe, Ivan V. Oseledets:
Low-rank surrogate modeling and stochastic zero-order optimization for training of neural networks with black-box layers. CoRR abs/2509.15113 (2025) - [i19]Evgenia Shustova, Marina Sheshukova, Sergey Samsonov, Evgeny Frolov:
Scalable LinUCB: Low-Rank Design Matrix Updates for Recommenders with Large Action Spaces. CoRR abs/2510.19349 (2025) - [i18]Daria Cherniuk, Nikita Sukhorukov, Nikita Sushko, Daniil Gusak, Danil Sivtsov, Elena Tutubalina, Evgeny Frolov:
LLavaCode: Compressed Code Representations for Retrieval-Augmented Code Generation. CoRR abs/2510.19644 (2025) - [i17]Ivan Razvorotnev, Marina Munkhoeva, Evgeny Frolov:
Barlow Twins for Sequential Recommendation. CoRR abs/2510.26407 (2025) - 2024
- [j3]Albert Saiapin, Gleb Balitskiy, Daniel Bershatsky, Aleksandr Katrutsa, Evgeny Frolov, Alexey A. Frolov, Ivan V. Oseledets, Vitaliy Kharin:
Federated privacy-preserving collaborative filtering for on-device next app prediction. User Model. User Adapt. Interact. 34(4): 1369-1398 (2024) - [c10]Danil Gusak, Gleb Mezentsev, Ivan V. Oseledets, Evgeny Frolov:
RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential Recommenders. CIKM 2024: 3772-3776 - [c9]Abdulaziz Samra, Evgeny Frolov, Alexey Vasilev, Alexander Grigorevskiy, Anton Vakhrushev:
Cross-Domain Latent Factors Sharing via Implicit Matrix Factorization. RecSys 2024: 309-317 - [c8]Gleb Mezentsev, Danil Gusak, Ivan V. Oseledets, Evgeny Frolov:
Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs. RecSys 2024: 475-485 - [c7]Evgeny Frolov, Tatyana Matveeva, Leyla Mirvakhabova, Ivan V. Oseledets:
Self-Attentive Sequential Recommendations with Hyperbolic Representations. RecSys 2024: 981-986 - [c6]Vladimir Baikalov, Evgeny Frolov:
End-to-End Graph-Sequential Representation Learning for Accurate Recommendations. WWW (Companion Volume) 2024: 501-504 - [i16]Vladimir Baikalov, Evgeny Frolov:
End-to-End Graph-Sequential Representation Learning for Accurate Recommendations. CoRR abs/2403.00895 (2024) - [i15]Danil Gusak, Gleb Mezentsev, Ivan V. Oseledets, Evgeny Frolov:
RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential Recommenders. CoRR abs/2408.02354 (2024) - [i14]Abdulaziz Samra, Evgeny Frolov, Alexey Vasilev, Alexander Grigorievskiy, Anton Vakhrushev:
Cross-Domain Latent Factors Sharing via Implicit Matrix Factorization. CoRR abs/2409.15568 (2024) - [i13]Gleb Mezentsev, Danil Gusak, Ivan V. Oseledets, Evgeny Frolov:
Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs. CoRR abs/2409.18721 (2024) - 2023
- [j2]Evgeny Frolov, Ivan V. Oseledets:
Tensor-Based Sequential Learning via Hankel Matrix Representation for Next Item Recommendations. IEEE Access 11: 6357-6371 (2023) - [i12]Yuliya Tukmacheva, Ivan V. Oseledets, Evgeny Frolov:
Mitigating Human and Computer Opinion Fraud via Contrastive Learning. CoRR abs/2301.03025 (2023) - [i11]Albert Sayapin, Gleb Balitskiy, Daniel Bershatsky, Aleksandr Katrutsa, Evgeny Frolov, Alexey A. Frolov, Ivan V. Oseledets, Vitaliy Kharin:
Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction. CoRR abs/2303.04744 (2023) - [i10]Albert Saiapin, Ivan V. Oseledets, Evgeny Frolov:
Dynamic Collaborative Filtering for Matrix- and Tensor-based Recommender Systems. CoRR abs/2312.10064 (2023) - 2022
- [c5]Viktoria Chekalina, Anton Razzhigaev, Albert Sayapin, Evgeny Frolov, Alexander Panchenko:
MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering. ACL (student) 2022: 355-365 - [i9]Artyom Nikitin, Andrei Chertkov, Rafael Ballester-Ripoll, Ivan V. Oseledets, Evgeny Frolov:
Are Quantum Computers Practical Yet? A Case for Feature Selection in Recommender Systems using Tensor Networks. CoRR abs/2205.04490 (2022) - [i8]Nikita Marin, Elizaveta Makhneva, Maria Lysyuk, Vladimir Chernyy, Ivan V. Oseledets, Evgeny Frolov:
Tensor-based Collaborative Filtering With Smooth Ratings Scale. CoRR abs/2205.05070 (2022) - [i7]Evgeny Frolov, Ivan V. Oseledets:
Tensor-based Sequential Learning via Hankel Matrix Representation for Next Item Recommendations. CoRR abs/2212.05720 (2022) - 2021
- [c4]Oluwafemi Olaleke, Ivan V. Oseledets, Evgeny Frolov:
Dynamic Modeling of User Preferences for Stable Recommendations. UMAP 2021: 262-266 - [i6]Oluwafemi Olaleke, Ivan V. Oseledets, Evgeny Frolov:
Dynamic Modeling of User Preferences for Stable Recommendations. CoRR abs/2104.05047 (2021) - 2020
- [c3]Leyla Mirvakhabova, Evgeny Frolov, Valentin Khrulkov, Ivan V. Oseledets, Alexander Tuzhilin:
Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks. RecSys 2020: 527-532 - [i5]Leyla Mirvakhabova, Evgeny Frolov, Valentin Khrulkov, Ivan V. Oseledets, Alexander Tuzhilin:
Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks. CoRR abs/2008.06716 (2020)
2010 – 2019
- 2019
- [c2]Evgeny Frolov, Ivan V. Oseledets:
HybridSVD: when collaborative information is not enough. RecSys 2019: 331-339 - 2018
- [p1]Evgeny Frolov, Ivan V. Oseledets:
Matrix Factorization for Collaborative Recommendations. Collaborative Recommendations 2018: 35-78 - [i4]Evgeny Frolov, Ivan V. Oseledets:
HybridSVD: When Collaborative Information is Not Enough. CoRR abs/1802.06398 (2018) - [i3]Evgeny Frolov, Ivan V. Oseledets:
Revealing the Unobserved by Linking Collaborative Behavior and Side Knowledge. CoRR abs/1807.10634 (2018) - 2017
- [j1]Evgeny Frolov, Ivan V. Oseledets:
Tensor methods and recommender systems. WIREs Data Mining Knowl. Discov. 7(3) (2017) - 2016
- [c1]Evgeny Frolov, Ivan V. Oseledets:
Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks. RecSys 2016: 91-98 - [i2]Evgeny Frolov, Ivan V. Oseledets:
Tensor Methods and Recommender Systems. CoRR abs/1603.06038 (2016) - [i1]Evgeny Frolov, Ivan V. Oseledets:
Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks. CoRR abs/1607.04228 (2016)
Coauthor Index
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last updated on 2026-01-07 22:07 CET by the dblp team
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