Julia Gusak - RankMe

24 papers A* 5C 1Journal 16Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	HiRemate: Hierarchical Approach for Efficient Re-materialization of Neural Networks. ICML Julia Gusak, Xunyi Zhao, Théotime Le Hellard, Zhe Li, Lionel Eyraud-Dubois, Olivier Beaumont
2024	J	`jnl`	Quantization Aware Factorization for Deep Neural Network Compression. J. Artif. Intell. Res. Daria Cherniuk, Stanislav Abukhovich, Anh Huy Phan, Ivan V. Oseledets, Andrzej Cichocki, Julia Gusak
2023	C	`conf`	Efficient GPT Model Pre-training using Tensor Train Matrix Representation. PACLIC Viktoria Chekalina, Georgiy Novikov, Julia Gusak, Alexander Panchenko, Ivan V. Oseledets
2023	J	`jnl`	Efficient GPT Model Pre-training using Tensor Train Matrix Representation. CoRR Viktoria Chekalina, Georgii S. Novikov, Julia Gusak, Ivan V. Oseledets, Alexander Panchenko
2023	A*	`conf`	Few-bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction. ICML Georgii Sergeevich Novikov, Daniel Bershatsky, Julia Gusak, Alex Shonenkov, Denis Valerievich Dimitrov, Ivan V. Oseledets
2023	J	`jnl`	Quantization Aware Factorization for Deep Neural Network Compression. CoRR Daria Cherniuk, Stanislav Abukhovich, Anh Huy Phan, Ivan V. Oseledets, Andrzej Cichocki, Julia Gusak
2023	A*	`conf`	Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch. ICML Xunyi Zhao, Théotime Le Hellard, Lionel Eyraud-Dubois, Julia Gusak, Olivier Beaumont
2023	J	`jnl`	Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch. CoRR Xunyi Zhao, Théotime Le Hellard, Lionel Eyraud, Julia Gusak, Olivier Beaumont
2022	J	`jnl`	Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction. CoRR Georgii S. Novikov, Daniel Bershatsky, Julia Gusak, Alex Shonenkov, Denis Dimitrov, Ivan V. Oseledets
2022	J	`jnl`	Memory-Efficient Backpropagation through Large Linear Layers. CoRR Daniel Bershatsky, Aleksandr Mikhalev, Alexandr Katrutsa, Julia Gusak, Daniil Merkulov, Ivan V. Oseledets
2022	A*	`conf`	Survey on Efficient Training of Large Neural Networks. IJCAI Julia Gusak, Daria Cherniuk, Alena Shilova, Alexandr Katrutsa, Daniel Bershatsky, Xunyi Zhao, Lionel Eyraud-Dubois, Oleh Shliazhko, Denis Dimitrov, Ivan V. Oseledets, Olivier Beaumont
2022	J	`jnl`	Survey on Large Scale Neural Network Training. CoRR Julia Gusak, Daria Cherniuk, Alena Shilova, Alexandr Katrutsa, Daniel Bershatsky, Xunyi Zhao, Lionel Eyraud-Dubois, Oleg Shlyazhko, Denis Dimitrov, Ivan V. Oseledets, Olivier Beaumont
2021	J	`jnl`	Meta-Solver for Neural Ordinary Differential Equations. CoRR Julia Gusak, Alexandr Katrutsa, Talgat Daulbaev, Andrzej Cichocki, Ivan V. Oseledets
2020	J	`jnl`	Active Subspace of Neural Networks: Structural Analysis and Universal Attacks. SIAM J. Math. Data Sci. Chunfeng Cui, Kaiqi Zhang, Talgat Daulbaev, Julia Gusak, Ivan V. Oseledets, Zheng Zhang
2020	J	`jnl`	Interpolated Adjoint Method for Neural ODEs. CoRR Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki, Ivan V. Oseledets
2020	A*	`conf`	Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs. NeurIPS Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki, Ivan V. Oseledets
2020	—	`conf`	Stable Low-Rank Tensor Decomposition for Compression of Convolutional Neural Network. ECCV (29) Anh Huy Phan, Konstantin Sobolev, Konstantin Sozykin, Dmitry Ermilov, Julia Gusak, Petr Tichavský, Valeriy Glukhov, Ivan V. Oseledets, Andrzej Cichocki
2020	J	`jnl`	Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network. CoRR Anh Huy Phan, Konstantin Sobolev, Konstantin Sozykin, Dmitry Ermilov, Julia Gusak, Petr Tichavský, Valeriy Glukhov, Ivan V. Oseledets, Andrzej Cichocki
2020	J	`jnl`	Towards Understanding Normalization in Neural ODEs. CoRR Julia Gusak, Larisa Markeeva, Talgat Daulbaev, Alexandr Katrutsa, Andrzej Cichocki, Ivan V. Oseledets
2019	J	`jnl`	Active Subspace of Neural Networks: Structural Analysis and Universal Attacks. CoRR Chunfeng Cui, Kaiqi Zhang, Talgat Daulbaev, Julia Gusak, Ivan V. Oseledets, Zheng Zhang
2019	—	`conf`	Automated Multi-Stage Compression of Neural Networks. ICCV Workshops Julia Gusak, Maksym Kholyavchenko, Evgeny Ponomarev, Larisa Markeeva, Philip Blagoveschensky, Andrzej Cichocki, Ivan V. Oseledets
2019	J	`jnl`	One time is not enough: iterative tensor decomposition for neural network compression. CoRR Julia Gusak, Maksym Kholyavchenko, Evgeny Ponomarev, Larisa Markeeva, Ivan V. Oseledets, Andrzej Cichocki
2019	J	`jnl`	Reduced-Order Modeling of Deep Neural Networks. CoRR Talgat Daulbaev, Julia Gusak, Evgeny Ponomarev, Andrzej Cichocki, Ivan V. Oseledets
2016	J	`jnl`	Optimal Control and Sensitivity Analysis for Two Risk Models. Commun. Stat. Simul. Comput. Ekaterina Bulinskaya, Julia Gusak