Sergey Kolesnikov

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 46

Top Topics

Item Recommendation

Reinforcement Learning

Top Venues

Publications

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 (2024)
Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov
EXACT: How to train your accuracy. Pattern Recognit. Lett. 185 (2024)
Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov
Probabilistic embeddings revisited. Vis. Comput. 40 (6) (2024)
Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov
Katakomba: Tools and Benchmarks for Data-Driven NetHack. CoRR (2023)
Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov
Revisiting the Minimalist Approach to Offline Reinforcement Learning. CoRR (2023)
Sergey Naumov, Marina Ananyeva, Oleg Lashinin, Sergey Kolesnikov, Dmitry I. Ignatov
Time-Dependent Next-Basket Recommendations. ECIR (2) (2023)
Veronika Ivanova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
RecBaselines2023: a new dataset for choosing baselines for recommender models. CoRR (2023)
Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov
Revisiting the Minimalist Approach to Offline Reinforcement Learning. NeurIPS (2023)
Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov
Anti-Exploration by Random Network Distillation. ICML (2023)
Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. CoRR (2023)
Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov
Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy. CoRR (2023)
Elizaveta Makhneva, Anna Sverkunova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
Make your next item recommendation model time sensitive. UMAP (Adjunct Publication) (2023)
Aleksey Romanov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
Time-Aware Item Weighting for the Next Basket Recommendations. RecSys (2023)
Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov
In-Context Reinforcement Learning for Variable Action Spaces. CoRR (2023)
Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov
Anti-Exploration by Random Network Distillation. CoRR (2023)
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)
Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov
Emergence of In-Context Reinforcement Learning from Noise Distillation. CoRR (2023)
Veronika Ivanova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
RecBaselines2023: a new dataset for choosing baselines for recommender models. BIR@ECIR (2023)
Maksim Zhdanov, Stanislav Dereka, Sergey Kolesnikov
Unveiling Empirical Pathologies of Laplace Approximation for Uncertainty Estimation. CoRR (2023)
Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov
CORL: Research-oriented Deep Offline Reinforcement Learning Library. NeurIPS (2023)
Denis Krasilnikov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
Next-basket Recommendation Constrained by Total Cost. ORSUM@RecSys (2023)
Sergey Kolesnikov
Wild-Tab: A Benchmark For Out-Of-Distribution Generalization In Tabular Regression. CoRR (2023)
Aleksey Romanov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
Time-Aware Item Weighting for the Next Basket Recommendations. CoRR (2023)
Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov
Katakomba: Tools and Benchmarks for Data-Driven NetHack. NeurIPS (2023)
Oleg Lashinin, Kirill Bykov, Marina Ananyeva, Sergey Kolesnikov
GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram. KaRS@RecSys (2023)
Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov
Deep Image Retrieval is not Robust to Label Noise. CoRR (2022)
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 (2022)
Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov
EXACT: How to Train Your Accuracy. CoRR (2022)
Sergey Kolesnikov, Mikhail Andronov
CVTT: Cross-Validation Through Time. CoRR (2022)
Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov
Probabilistic Embeddings Revisited. CoRR (2022)
Marina Ananyeva, Oleg Lashinin, Veronika Ivanova, Sergey Kolesnikov, Dmitry I. Ignatov
Towards Interaction-based User Embeddings in Sequential Recommender Models. ORSUM@RecSys (2022)
Vladislav Kurenkov, Sergey Kolesnikov
Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters. ICML (2022)
Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov
CORL: Research-oriented Deep Offline Reinforcement Learning Library. CoRR (2022)
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 (2022)
Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov
Deep Image Retrieval is not Robust to Label Noise. CVPR Workshops (2022)
Evgeniy Egorov, Vasily Kostyumov, Mikhail Konyk, Sergey Kolesnikov
LRWR: Large-Scale Benchmark for Lip Reading in Russian language. CoRR (2021)
Vladislav Kurenkov, Sergey Kolesnikov
Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters. CoRR (2021)
Sergey Kolesnikov, Oleg Lashinin, Michail Pechatov, Alexander Kosov
TTRS: Tinkoff Transactions Recommender System benchmark. CoRR (2021)
Sergey Kolesnikov, Valentin Khrulkov
Sample Efficient Ensemble Learning with Catalyst.RL. CoRR (2020)
Sergey Kolesnikov, Oleksii Hrinchuk
Catalyst.RL: A Distributed Framework for Reproducible RL Research. CoRR (2019)
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 (2019)
Sergey Kolesnikov, Eriko Fukumoto, Barry Bozeman
Researchers' risk-smoothing publication strategies: Is productivity the enemy of impact? Scientometrics 116 (3) (2018)
Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis
Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation. AAAI Spring Symposia (2018)
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 (2018)
Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis
Run, skeleton, run: skeletal model in a physics-based simulation. CoRR (2017)
Yuri Parshin, Sergey Kolesnikov
Adaptive filtration of random signals in active antenna array with nonlinear transmit/receive modules. ICUMT (2016)