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Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction.

G. Novikov, D. Bershatsky, J. Gusak, A. Shonenkov, D. Dimitrov, and I. Oseledets. CoRR, (2022)

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Daniel

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LoTR: Low Tensor Rank Weight Adaptation.D. Bershatsky, D. Cherniuk, T. Daulbaev, A. Mikhalev, and I. Oseledets. CoRR, (2024)NAG-GS: Semi-Implicit, Accelerated and Robust Stochastic Optimizers.V. Leplat, D. Merkulov, A. Katrutsa, D. Bershatsky, and I. Oseledets. CoRR, (2022)Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction.G. Novikov, D. Bershatsky, J. Gusak, A. Shonenkov, D. Dimitrov, and I. Oseledets. CoRR, (2022)Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction.A. Sayapin, G. Balitskiy, D. Bershatsky, A. Katrutsa, E. Frolov, A. Frolov, I. Oseledets, and V. Kharin. CoRR, (2023)Survey on Efficient Training of Large Neural Networks.J. Gusak, D. Cherniuk, A. Shilova, A. Katrutsa, D. Bershatsky, X. Zhao, L. Eyraud-Dubois, O. Shliazhko, D. Dimitrov, I. Oseledets and 1 other author(s). IJCAI, page 5494-5501. ijcai.org, (2022)Survey on Large Scale Neural Network Training.J. Gusak, D. Cherniuk, A. Shilova, A. Katrutsa, D. Bershatsky, X. Zhao, L. Eyraud-Dubois, O. Shlyazhko, D. Dimitrov, I. Oseledets and 1 other author(s). CoRR, (2022)Memory-Efficient Backpropagation through Large Linear Layers.D. Bershatsky, A. Mikhalev, A. Katrutsa, J. Gusak, D. Merkulov, and I. Oseledets. CoRR, (2022)Few-bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction.G. Novikov, D. Bershatsky, J. Gusak, A. Shonenkov, D. Dimitrov, and I. Oseledets. ICML, volume 202 of Proceedings of Machine Learning Research, page 26363-26381. PMLR, (2023)

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Disambiguation of "Bershatsky, Daniel"

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Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction.

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Daniel

Daniel

Daniel Dirkmann

Daniel Stanze

Daniel Wied

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Disambiguation of "Bershatsky, Daniel"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction.

Please choose a person to relate this publication to

Daniel

Daniel

Daniel Dirkmann

Daniel Stanze

Daniel Wied

Other publications of authors with the same name

Disambiguation

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URL
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Chicago
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Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction.