Oseledets, Ivan V.

14 publications

IJCAI 2025 AI Diagnostic Assistant (AIDA): A Predictive Model for Diagnoses from Health Records in Clinical Decision Support Systems Dmitriy Umerenkov, Alexandr Nesterov, Vladimir Shaposhnikov, Ruslan Abramov, Nikolay Romanenko, Vladimir Kokh, Marina Kirina, Anton Abrosimov, Dmitry V. Dylov, Ivan V. Oseledets

AAAI 2025 Certification of Speaker Recognition Models to Additive Perturbations Dmitrii Korzh, Elvir Karimov, Mikhail Pautov, Oleg Y. Rogov, Ivan V. Oseledets

IJCAI 2024 Probabilistically Robust Watermarking of Neural Networks Mikhail Pautov, Nikita Bogdanov, Stanislav Pyatkin, Oleg Rogov, Ivan V. Oseledets

JAIR 2024 Quantization Aware Factorization for Deep Neural Network Compression Daria Cherniuk, Stanislav Abukhovich, Anh Huy Phan, Ivan V. Oseledets, Andrzej Cichocki, Julia Gusak

AAAI 2022 CC-CERT: A Probabilistic Approach to Certify General Robustness of Neural Networks Mikhail Pautov, Nurislam Tursynbek, Marina Munkhoeva, Nikita Muravev, Aleksandr Petiushko, Ivan V. Oseledets

IJCAI 2022 Survey on Efficient Training of Large Neural Networks Julia Gusak, Daria Cherniuk, Alena Shilova, Alexandr Katrutsa, Daniel Bershatsky, Xunyi Zhao, Lionel Eyraud-Dubois, Oleh Shliazhko, Denis Dimitrov, Ivan V. Oseledets, Olivier Beaumont

AAAI 2021 Adversarial Turing Patterns from Cellular Automata Nurislam Tursynbek, Ilya Vilkoviskiy, Maria Sindeeva, Ivan V. Oseledets

ICCVW 2021 Object-Based Augmentation for Building Semantic Segmentation: Ventura and Santa Rosa Case Study Svetlana Illarionova, Sergey Nesteruk, Dmitrii Shadrin, Vladimir Ignatiev, Mariia Pukalchik, Ivan V. Oseledets

UAI 2021 Tensor-Train Density Estimation Georgii S. Novikov, Maxim E. Panov, Ivan V. Oseledets

ICCVW 2019 Automated Multi-Stage Compression of Neural Networks Julia Gusak, Maksym Kholyavchenko, Evgeny Ponomarev, Larisa Markeeva, Philip Blagoveschensky, Andrzej Cichocki, Ivan V. Oseledets

ICLR 2017 Exponential Machines Alexander Novikov, Mikhail Trofimov, Ivan V. Oseledets

FnTML 2017 Tensor Networks for Dimensionality Reduction and Large-Scale Optimization: Part 2 Applications and Future Perspectives Andrzej Cichocki, Anh Huy Phan, Qibin Zhao, Namgil Lee, Ivan V. Oseledets, Masashi Sugiyama, Danilo P. Mandic

FnTML 2016 Tensor Networks for Dimensionality Reduction and Large-Scale Optimization: Part 1 Low-Rank Tensor Decompositions Andrzej Cichocki, Namgil Lee, Ivan V. Oseledets, Anh Huy Phan, Qibin Zhao, Danilo P. Mandic

ICLR 2015 Speeding-up Convolutional Neural Networks Using Fine-Tuned CP-Decomposition Vadim Lebedev, Yaroslav Ganin, Maksim Rakhuba, Ivan V. Oseledets, Victor S. Lempitsky