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Ivan Nazarov
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2020 – today
- 2024
- [i13]África Periáñez, Kathrin Schmitz, Lazola Makhupula, Moiz Hassan Khan, Moeti Moleko, Ana Fernández del Río, Ivan Nazarov, Aditya Rastogi, Dexian Tang:
Optimizing HIV Patient Engagement with Reinforcement Learning in Resource-Limited Settings. CoRR abs/2408.07629 (2024) - [i12]Ana Fernández del Río, Michael Brennan Leong, Paulo Saraiva, Ivan Nazarov, Aditya Rastogi, Moiz Hassan, Dexian Tang, África Periáñez:
Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services. CoRR abs/2408.07647 (2024) - [i11]Ana Fernández del Río, Michael Brennan Leong, Paulo Saraiva, Ivan Nazarov, Aditya Rastogi, Moiz Hassan, Dexian Tang, África Periáñez:
Adaptive User Journeys in Pharma E-Commerce with Reinforcement Learning: Insights from SwipeRx. CoRR abs/2408.08024 (2024) - [i10]África Periáñez, Ana Fernández del Río, Ivan Nazarov, Enric Jané, Moiz Hassan, Aditya Rastogi, Dexian Tang:
The Digital Transformation in Health: How AI Can Improve the Performance of Health Systems. CoRR abs/2409.16098 (2024) - 2022
- [j1]Alexander Ponomarchuk, Ilya Burenko, Elian Malkin, Ivan Nazarov, Vladimir Kokh, Manvel Avetisian, Leonid Zhukov:
Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough. IEEE J. Sel. Top. Signal Process. 16(2): 175-187 (2022) - [c9]Dmitrii Babaev, Nikita Ovsov, Ivan Kireev, Mariya Ivanova, Gleb Gusev, Ivan Nazarov, Alexander Tuzhilin:
CoLES: Contrastive Learning for Event Sequences with Self-Supervision. SIGMOD Conference 2022: 1190-1199 - [i9]Eric Hambro, Sharada P. Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, DaeJin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Küttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Parker-Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktäschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin, Maciej Sypetkowski, Michal Sypetkowski:
Insights From the NeurIPS 2021 NetHack Challenge. CoRR abs/2203.11889 (2022) - 2021
- [c8]Eric Hambro, Sharada P. Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, DaeJin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Küttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Parker-Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktäschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin, Maciej Sypetkowski, Michal Sypetkowski:
Insights From the NeurIPS 2021 NetHack Challenge. NeurIPS (Competition and Demos) 2021: 41-52 - [i8]Alexander Ponomarchuk, Ilya Burenko, Elian Malkin, Ivan Nazarov, Vladimir Kokh, Manvel Avetisian, Leonid Zhukov:
Project Achoo: A Practical Model and Application for COVID-19 Detection from Recordings of Breath, Voice, and Cough. CoRR abs/2107.10716 (2021) - 2020
- [c7]Ivan Nazarov, Evgeny Burnaev:
Bayesian Sparsification of Deep C-valued Networks. ICML 2020: 7230-7242 - [i7]Ivan Nazarov, Evgeny Burnaev:
Bayesian Sparsification Methods for Deep Complex-valued Networks. CoRR abs/2003.11413 (2020) - [i6]Rodrigo Rivera-Castro, Aleksandr Pletnev, Polina Pilyugina, Grecia Diaz, Ivan Nazarov, Wanyi Zhu, Evgeny Burnaev:
Topology-based Clusterwise Regression for User Segmentation and Demand Forecasting. CoRR abs/2009.03661 (2020)
2010 – 2019
- 2019
- [c6]Rodrigo Rivera-Castro, Aleksandr Pletnev, Polina Pilyugina, Grecia Diaz, Ivan Nazarov, Wanyi Zhu, Evgeny Burnaev:
Topology-Based Clusterwise Regression for User Segmentation and Demand Forecasting. DSAA 2019: 326-336 - [c5]Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang, Ivan Maksimov, Aleksandr Pletnev, Evgeny Burnaev:
An Industry Case of Large-Scale Demand Forecasting of Hierarchical Components. ICMLA 2019: 134-139 - [c4]Denis Volkhonskiy, Ivan Nazarov, Evgeny Burnaev:
Steganographic generative adversarial networks. ICMV 2019: 114333M - [c3]Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang, Alexander Pletneev, Ivan Maksimov, Evgeny Burnaev:
Demand Forecasting Techniques for Build-to-Order Lean Manufacturing Supply Chains. ISNN (1) 2019: 213-222 - [i5]Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang, Alexander Pletneev, Ivan Maksimov, Evgeny Burnaev:
Demand forecasting techniques for build-to-order lean manufacturing supply chains. CoRR abs/1905.07902 (2019) - 2018
- [i4]Ivan Nazarov, Boris Shirokikh, Maria Burkina, Gennady Fedonin, Maxim Panov:
Sparse Group Inductive Matrix Completion. CoRR abs/1804.10653 (2018) - 2017
- [c2]Vladislav Ishimtsev, Alexander Bernstein, Evgeny Burnaev, Ivan Nazarov:
Conformal k-NN Anomaly Detector for Univariate Data Streams. COPA 2017: 213-227 - [i3]Denis Volkhonskiy, Ivan Nazarov, Boris Borisenko, Evgeny Burnaev:
Steganographic Generative Adversarial Networks. CoRR abs/1703.05502 (2017) - [i2]Vladislav Ishimtsev, Ivan Nazarov, Alexander Bernstein, Evgeny Burnaev:
Conformal k-NN Anomaly Detector for Univariate Data Streams. CoRR abs/1706.03412 (2017) - 2016
- [c1]Evgeny Burnaev, Ivan Nazarov:
Conformalized Kernel Ridge Regression. ICMLA 2016: 45-52 - [i1]Evgeny Burnaev, Ivan Nazarov:
Conformalized Kernel Ridge Regression. CoRR abs/1609.05959 (2016)
Coauthor Index
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last updated on 2024-10-17 20:25 CEST by the dblp team
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