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ORCIDDenis Kuznedelev
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2020 – today
- 2024
[j1]Denis Kuznedelev, Eldar Kurtic, Eugenia Iofinova, Elias Frantar, Alexandra Peste, Dan Alistarh:
Accurate Neural Network Pruning Requires Rethinking Sparse Optimization. Trans. Mach. Learn. Res. 2024 (2024)- [c7]Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh:
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression. ICLR 2024 - [c6]Vage Egiazarian, Andrei Panferov, Denis Kuznedelev, Elias Frantar, Artem Babenko, Dan Alistarh:
Extreme Compression of Large Language Models via Additive Quantization. ICML 2024 - [i15]Vage Egiazarian, Andrei Panferov, Denis Kuznedelev, Elias Frantar, Artem Babenko, Dan Alistarh:
Extreme Compression of Large Language Models via Additive Quantization. CoRR abs/2401.06118 (2024) - [i14]Sergey Kastryulin, Artem Konev, Alexander Shishenya, Eugene Lyapustin, Artem Khurshudov, Alexander Tselousov, Nikita Vinokurov, Denis Kuznedelev, Alexander Markovich, Grigoriy Livshits, Alexey Kirillov, Anastasiia Tabisheva, Liubov Chubarova, Marina Kaminskaia, Alexander Ustyuzhanin
, Artemii Shvetsov, Daniil Shlenskii, Valerii Startsev, Dmitrii Kornilov, Mikhail Romanov, Artem Babenko, Sergei Ovcharenko, Valentin Khrulkov:
YaART: Yet Another ART Rendering Technology. CoRR abs/2404.05666 (2024) - [i13]Vladimir Malinovskii, Denis Mazur, Ivan Ilin, Denis Kuznedelev, Konstantin Burlachenko, Kai Yi, Dan Alistarh, Peter Richtárik:
PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression. CoRR abs/2405.14852 (2024) - [i12]Denis Kuznedelev, Valerii Startsev, Daniil Shlenskii, Sergey Kastryulin:
Does Diffusion Beat GAN in Image Super Resolution? CoRR abs/2405.17261 (2024) - [i11]Diyuan Wu, Ionut-Vlad Modoranu, Mher Safaryan, Denis Kuznedelev, Dan Alistarh:
The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information. CoRR abs/2408.17163 (2024) - [i10]Vage Egiazarian, Denis Kuznedelev, Anton Voronov, Ruslan Svirschevski, Michael Goin, Daniil Pavlov, Dan Alistarh, Dmitry Baranchuk:
Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization. CoRR abs/2409.00492 (2024) - 2023
- [c5]Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova:
A critical look at the evaluation of GNNs under heterophily: Are we really making progress? ICLR 2023 - [c4]Maksim Velikanov, Denis Kuznedelev, Dmitry Yarotsky:
A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta. ICLR 2023 - [c3]Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova:
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts. NeurIPS 2023 - [c2]Denis Kuznedelev, Eldar Kurtic, Elias Frantar, Dan Alistarh:
CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models. NeurIPS 2023 - [c1]Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova:
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond. NeurIPS 2023 - [i9]Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova:
A critical look at the evaluation of GNNs under heterophily: are we really making progress? CoRR abs/2302.11640 (2023) - [i8]Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova:
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts. CoRR abs/2302.13875 (2023) - [i7]Denis Kuznedelev, Soroush Tabesh, Kimia Noorbakhsh, Elias Frantar, Sara Beery, Eldar Kurtic, Dan Alistarh:
Vision Models Can Be Efficiently Specialized via Few-Shot Task-Aware Compression. CoRR abs/2303.14409 (2023) - [i6]Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh:
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression. CoRR abs/2306.03078 (2023) - [i5]Denis Kuznedelev, Eldar Kurtic, Eugenia Iofinova, Elias Frantar, Alexandra Peste, Dan Alistarh:
Accurate Neural Network Pruning Requires Rethinking Sparse Optimization. CoRR abs/2308.02060 (2023) - [i4]Eldar Kurtic, Denis Kuznedelev, Elias Frantar, Michael Goin, Dan Alistarh:
Sparse Fine-tuning for Inference Acceleration of Large Language Models. CoRR abs/2310.06927 (2023) - 2022
- [i3]Maksim Velikanov, Denis Kuznedelev, Dmitry Yarotsky:
A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta. CoRR abs/2206.11124 (2022) - [i2]Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova:
Characterizing Graph Datasets for Node Classification: Beyond Homophily-Heterophily Dichotomy. CoRR abs/2209.06177 (2022) - [i1]Denis Kuznedelev, Eldar Kurtic, Elias Frantar, Dan Alistarh:
oViT: An Accurate Second-Order Pruning Framework for Vision Transformers. CoRR abs/2210.09223 (2022)
Coauthor Index
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