Sergey Kolesnikov

Orcid: 0000-0002-4820-987X

According to our database1, Sergey Kolesnikov authored at least 36 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Probabilistic embeddings revisited.
Vis. Comput., June, 2024

EXACT: How to train your accuracy.
Pattern Recognit. Lett., 2024

XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning.
CoRR, 2024

Revisiting BPR: A Replicability Study of a Common Recommender System Baseline.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Emergence of In-Context Reinforcement Learning from Noise Distillation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

In-Context Reinforcement Learning for Variable Action Spaces.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX.
CoRR, 2023

Unveiling Empirical Pathologies of Laplace Approximation for Uncertainty Estimation.
CoRR, 2023

Wild-Tab: A Benchmark For Out-Of-Distribution Generalization In Tabular Regression.
CoRR, 2023

Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy.
CoRR, 2023

Make your next item recommendation model time sensitive.
Proceedings of the Adjunct Proceedings of the 31st ACM Conference on User Modeling, 2023

Time-Aware Item Weighting for the Next Basket Recommendations.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Next-basket Recommendation Constrained by Total Cost.
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.
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.
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.
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.
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.
Proceedings of the International Conference on Machine Learning, 2023

Time-Dependent Next-Basket Recommendations.
Proceedings of the Advances in Information Retrieval, 2023

Utilising Crowdsourcing to Assess the Effectiveness of Item-based Explanations of Merchant Recommendations.
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.
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.
CoRR, 2022

Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size.
CoRR, 2022

CVTT: Cross-Validation Through Time.
CoRR, 2022

Towards Interaction-based User Embeddings in Sequential Recommender Models.
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.
Proceedings of the International Conference on Machine Learning, 2022

Deep Image Retrieval is not Robust to Label Noise.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
TTRS: Tinkoff Transactions Recommender System benchmark.
CoRR, 2021

LRWR: Large-Scale Benchmark for Lip Reading in Russian language.
CoRR, 2021

2020
Sample Efficient Ensemble Learning with Catalyst.RL.
CoRR, 2020

2019
Catalyst.RL: A Distributed Framework for Reproducible RL Research.
CoRR, 2019

Artificial Intelligence for Prosthetics - challenge solutions.
CoRR, 2019

2018
Researchers' risk-smoothing publication strategies: Is productivity the enemy of impact?
Scientometrics, 2018

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments.
CoRR, 2018

Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation.
Proceedings of the 2018 AAAI Spring Symposia, 2018

2016
Adaptive filtration of random signals in active antenna array with nonlinear transmit/receive modules.
Proceedings of the 8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, 2016


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