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ORCIDSergey Kolesnikov
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2020 – today
- 2024
[j3]Ivan Karpukhin
, Stanislav Dereka, Sergey Kolesnikov:
EXACT: How to train your accuracy. Pattern Recognit. Lett. 185: 23-30 (2024)- [j2]Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov:
Probabilistic embeddings revisited. Vis. Comput. 40(6): 4373-4386 (2024) - [c19]Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov:
In-Context Reinforcement Learning for Variable Action Spaces. ICML 2024 - [c18]Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov:
Emergence of In-Context Reinforcement Learning from Noise Distillation. ICML 2024 - [c17]Aleksandr Milogradskii, Oleg Lashinin, Alexander P, Marina Ananyeva, Sergey Kolesnikov:
Revisiting BPR: A Replicability Study of a Common Recommender System Baseline. RecSys 2024: 267-277 - [i28]Alexander Nikulin, Ilya Zisman, Alexey Zemtsov, Viacheslav Sinii, Vladislav Kurenkov, Sergey Kolesnikov:
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning. CoRR abs/2406.08973 (2024) - [i27]Aleksandr Milogradskii, Oleg Lashinin, Alexander P, Marina Ananyeva, Sergey Kolesnikov:
Revisiting BPR: A Replicability Study of a Common Recommender System Baseline. CoRR abs/2409.14217 (2024) - 2023
- [c16]Veronika Ivanova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov:
RecBaselines2023: a new dataset for choosing baselines for recommender models. BIR@ECIR 2023: 52-65 - [c15]Denis Krasilnikov, Oleg Lashinin, Maksim Tsygankov, Marina Ananyeva, Sergey Kolesnikov:
Utilising Crowdsourcing to Assess the Effectiveness of Item-based Explanations of Merchant Recommendations. CSW@WSDM 2023: 77-86 - [c14]Sergey Naumov, Marina Ananyeva, Oleg Lashinin, Sergey Kolesnikov, Dmitry I. Ignatov:
Time-Dependent Next-Basket Recommendations. ECIR (2) 2023: 502-511 - [c13]Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov:
Anti-Exploration by Random Network Distillation. ICML 2023: 26228-26244 - [c12]Oleg Lashinin, Kirill Bykov, Marina Ananyeva, Sergey Kolesnikov:
GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram. KaRS@RecSys 2023: 35-43 - [c11]Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov:
Katakomba: Tools and Benchmarks for Data-Driven NetHack. NeurIPS 2023 - [c10]Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov:
Revisiting the Minimalist Approach to Offline Reinforcement Learning. NeurIPS 2023 - [c9]Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov:
CORL: Research-oriented Deep Offline Reinforcement Learning Library. NeurIPS 2023 - [c8]Denis Krasilnikov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov:
Next-basket Recommendation Constrained by Total Cost. ORSUM@RecSys 2023 - [c7]Aleksey Romanov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov:
Time-Aware Item Weighting for the Next Basket Recommendations. RecSys 2023: 985-992 - [c6]Elizaveta Makhneva, Anna Sverkunova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov:
Make your next item recommendation model time sensitive. UMAP (Adjunct Publication) 2023: 191-195 - [i26]Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov:
Anti-Exploration by Random Network Distillation. CoRR abs/2301.13616 (2023) - [i25]Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov:
Revisiting the Minimalist Approach to Offline Reinforcement Learning. CoRR abs/2305.09836 (2023) - [i24]Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov:
Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy. CoRR abs/2305.11616 (2023) - [i23]Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov:
Katakomba: Tools and Benchmarks for Data-Driven NetHack. CoRR abs/2306.08772 (2023) - [i22]Veronika Ivanova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov:
RecBaselines2023: a new dataset for choosing baselines for recommender models. CoRR abs/2306.14292 (2023) - [i21]Aleksey Romanov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov:
Time-Aware Item Weighting for the Next Basket Recommendations. CoRR abs/2307.16297 (2023) - [i20]Sergey Kolesnikov:
Wild-Tab: A Benchmark For Out-Of-Distribution Generalization In Tabular Regression. CoRR abs/2312.01792 (2023) - [i19]Maksim Zhdanov, Stanislav Dereka, Sergey Kolesnikov:
Unveiling Empirical Pathologies of Laplace Approximation for Uncertainty Estimation. CoRR abs/2312.10464 (2023) - [i18]Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov:
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. CoRR abs/2312.12044 (2023) - [i17]Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov:
Emergence of In-Context Reinforcement Learning from Noise Distillation. CoRR abs/2312.12275 (2023) - [i16]Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov:
In-Context Reinforcement Learning for Variable Action Spaces. CoRR abs/2312.13327 (2023) - 2022
- [c5]Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov:
Deep Image Retrieval is not Robust to Label Noise. CVPR Workshops 2022: 4971-4976 - [c4]Vladislav Kurenkov, Sergey Kolesnikov:
Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters. ICML 2022: 11729-11752 - [c3]Marina Ananyeva, Oleg Lashinin, Veronika Ivanova, Sergey Kolesnikov, Dmitry I. Ignatov:
Towards Interaction-based User Embeddings in Sequential Recommender Models. ORSUM@RecSys 2022 - [i15]Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov:
Probabilistic Embeddings Revisited. CoRR abs/2202.06768 (2022) - [i14]Sergey Kolesnikov, Mikhail Andronov:
CVTT: Cross-Validation Through Time. CoRR abs/2205.05393 (2022) - [i13]Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov:
EXACT: How to Train Your Accuracy. CoRR abs/2205.09615 (2022) - [i12]Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov:
Deep Image Retrieval is not Robust to Label Noise. CoRR abs/2205.11195 (2022) - [i11]Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov:
CORL: Research-oriented Deep Offline Reinforcement Learning Library. CoRR abs/2210.07105 (2022) - [i10]Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Dmitry Akimov, Sergey Kolesnikov:
Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size. CoRR abs/2211.11092 (2022) - [i9]Dmitriy Akimov, Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov:
Let Offline RL Flow: Training Conservative Agents in the Latent Space of Normalizing Flows. CoRR abs/2211.11096 (2022) - 2021
- [i8]Evgeniy Egorov, Vasily Kostyumov, Mikhail Konyk, Sergey Kolesnikov:
LRWR: Large-Scale Benchmark for Lip Reading in Russian language. CoRR abs/2109.06692 (2021) - [i7]Vladislav Kurenkov, Sergey Kolesnikov:
Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters. CoRR abs/2110.04156 (2021) - [i6]Sergey Kolesnikov, Oleg Lashinin, Michail Pechatov, Alexander Kosov:
TTRS: Tinkoff Transactions Recommender System benchmark. CoRR abs/2110.05589 (2021) - 2020
- [i5]Sergey Kolesnikov, Valentin Khrulkov:
Sample Efficient Ensemble Learning with Catalyst.RL. CoRR abs/2003.14210 (2020)
2010 – 2019
- 2019
- [i4]Lukasz Kidzinski, Carmichael F. Ong, Sharada Prasanna Mohanty, Jennifer L. Hicks, Sean F. Carroll, Bo Zhou, Hong-cheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaskowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy D. Watson, Marcel Salathé, Sergey Levine, Scott L. Delp:
Artificial Intelligence for Prosthetics - challenge solutions. CoRR abs/1902.02441 (2019) - [i3]Sergey Kolesnikov, Oleksii Hrinchuk:
Catalyst.RL: A Distributed Framework for Reproducible RL Research. CoRR abs/1903.00027 (2019) - 2018
- [j1]Sergey Kolesnikov, Eriko Fukumoto, Barry Bozeman:
Researchers' risk-smoothing publication strategies: Is productivity the enemy of impact? Scientometrics 116(3): 1995-2017 (2018) - [c2]Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis:
Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation. AAAI Spring Symposia 2018 - [i2]Lukasz Kidzinski, Sharada Prasanna Mohanty, Carmichael F. Ong, Zhewei Huang, Shuchang Zhou, Anton Pechenko, Adam Stelmaszczyk, Piotr Jarosik, Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis, Zhibo Chen, Zhizheng Zhang, Jiale Chen, Jun Shi, Zhuobin Zheng, Chun Yuan, Zhihui Lin, Henryk Michalewski, Piotr Milos, Blazej Osinski, Andrew Melnik, Malte Schilling, Helge J. Ritter, Sean F. Carroll, Jennifer L. Hicks, Sergey Levine, Marcel Salathé, Scott L. Delp:
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. CoRR abs/1804.00361 (2018) - 2017
- [i1]Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis:
Run, skeleton, run: skeletal model in a physics-based simulation. CoRR abs/1711.06922 (2017) - 2016
- [c1]Yuri Parshin, Sergey Kolesnikov:
Adaptive filtration of random signals in active antenna array with nonlinear transmit/receive modules. ICUMT 2016: 443-446
Coauthor Index
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last updated on 2024-10-30 20:33 CET by the dblp team
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