Sergey Kolesnikov

According to our database, Sergey Kolesnikov authored at least 34 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

In-Context Reinforcement Learning for Variable Action Spaces.

Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov

CoRR, 2023

Emergence of In-Context Reinforcement Learning from Noise Distillation.

Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov

CoRR, 2023

XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX.

Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov

CoRR, 2023

Unveiling Empirical Pathologies of Laplace Approximation for Uncertainty Estimation.

Maksim Zhdanov, Stanislav Dereka, Sergey Kolesnikov

CoRR, 2023

Wild-Tab: A Benchmark For Out-Of-Distribution Generalization In Tabular Regression.

Sergey Kolesnikov

CoRR, 2023

Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy.

Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov

CoRR, 2023

Make your next item recommendation model time sensitive.

Elizaveta Makhneva, Anna Sverkunova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov

Proceedings of the Adjunct Proceedings of the 31st ACM Conference on User Modeling, 2023

Time-Aware Item Weighting for the Next Basket Recommendations.

Aleksey Romanov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Next-basket Recommendation Constrained by Total Cost.

Denis Krasilnikov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov

Proceedings of the 6th Workshop on Online Recommender Systems and User Modeling co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

CORL: Research-oriented Deep Offline Reinforcement Learning Library.

Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Revisiting the Minimalist Approach to Offline Reinforcement Learning.

Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Katakomba: Tools and Benchmarks for Data-Driven NetHack.

Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram.

Oleg Lashinin, Kirill Bykov, Marina Ananyeva, Sergey Kolesnikov

Proceedings of the Fifth Knowledge-aware and Conversational Recommender Systems Workshop co-located with 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

Anti-Exploration by Random Network Distillation.

Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov

Proceedings of the International Conference on Machine Learning, 2023

Time-Dependent Next-Basket Recommendations.

Sergey Naumov, Marina Ananyeva, Oleg Lashinin, Sergey Kolesnikov, Dmitry I. Ignatov

Proceedings of the Advances in Information Retrieval, 2023

Utilising Crowdsourcing to Assess the Effectiveness of Item-based Explanations of Merchant Recommendations.

Denis Krasilnikov, Oleg Lashinin, Maksim Tsygankov, Marina Ananyeva, Sergey Kolesnikov

Proceedings of the 4th Crowd Science Workshop on Collaboration of Humans and Learning Algorithms for Data Labeling co-located with ACM International WSDM Conference (WSDM 2023), 2023

RecBaselines2023: a new dataset for choosing baselines for recommender models.

Veronika Ivanova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov

Proceedings of the 13th International Workshop on Bibliometric-enhanced Information Retrieval co-located with 45th European Conference on Information Retrieval (ECIR 2023), 2023

2022

Let Offline RL Flow: Training Conservative Agents in the Latent Space of Normalizing Flows.

Dmitriy Akimov, Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov

CoRR, 2022

Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size.

Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Dmitry Akimov, Sergey Kolesnikov

CoRR, 2022

EXACT: How to Train Your Accuracy.

Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov

CoRR, 2022

CVTT: Cross-Validation Through Time.

Sergey Kolesnikov, Mikhail Andronov

CoRR, 2022

Probabilistic Embeddings Revisited.

Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov

CoRR, 2022

Towards Interaction-based User Embeddings in Sequential Recommender Models.

Marina Ananyeva, Oleg Lashinin, Veronika Ivanova, Sergey Kolesnikov, Dmitry I. Ignatov

Proceedings of the 5th Workshop on Online Recommender Systems and User Modeling co-located with the 16th ACM Conference on Recommender Systems, 2022

Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters.

Vladislav Kurenkov, Sergey Kolesnikov

Proceedings of the International Conference on Machine Learning, 2022

Deep Image Retrieval is not Robust to Label Noise.

Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

TTRS: Tinkoff Transactions Recommender System benchmark.

Sergey Kolesnikov, Oleg Lashinin, Michail Pechatov, Alexander Kosov

CoRR, 2021

LRWR: Large-Scale Benchmark for Lip Reading in Russian language.

Evgeniy Egorov, Vasily Kostyumov, Mikhail Konyk, Sergey Kolesnikov

CoRR, 2021

2020

Sample Efficient Ensemble Learning with Catalyst.RL.

Sergey Kolesnikov, Valentin Khrulkov

CoRR, 2020

2019

Catalyst.RL: A Distributed Framework for Reproducible RL Research.

Sergey Kolesnikov, Oleksii Hrinchuk

CoRR, 2019

Artificial Intelligence for Prosthetics - challenge solutions.

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

CoRR, 2019

2018

Researchers' risk-smoothing publication strategies: Is productivity the enemy of impact?

Sergey Kolesnikov, Eriko Fukumoto, Barry Bozeman

Scientometrics, 2018

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments.

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

CoRR, 2018

Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation.

Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis

Proceedings of the 2018 AAAI Spring Symposia, 2018

2016

Adaptive filtration of random signals in active antenna array with nonlinear transmit/receive modules.

Yuri Parshin, Sergey Kolesnikov

Proceedings of the 8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, 2016