Evgenii Zheltonozhskii
Cited by
Cited by
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
Starcoder: may the source be with you!
R Li, LB Allal, Y Zi, N Muennighoff, D Kocetkov, C Mou, M Marone, C Akiki, ...
arXiv preprint arXiv:2305.06161, 2023
Uniq: Uniform noise injection for non-uniform quantization of neural networks
C Baskin, N Liss, E Schwartz, E Zheltonozhskii, R Giryes, AM Bronstein, ...
ACM Transactions on Computer Systems (TOCS) 37 (1-4), 1-15, 2021
Loss aware post-training quantization
Y Nahshan, B Chmiel, C Baskin, E Zheltonozhskii, R Banner, ...
Machine Learning 110 (11), 3245-3262, 2021
End-to-end referring video object segmentation with multimodal transformers
A Botach, E Zheltonozhskii, C Baskin
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
Contrast to divide: Self-supervised pre-training for learning with noisy labels
E Zheltonozhskii, C Baskin, A Mendelson, AM Bronstein, O Litany
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022
Nice: Noise injection and clamping estimation for neural network quantization
C Baskin, E Zheltonozhkii, T Rozen, N Liss, Y Chai, E Schwartz, R Giryes, ...
Mathematics 9 (17), 2144, 2021
Streaming architecture for large-scale quantized neural networks on an FPGA-based dataflow platform
C Baskin, N Liss, E Zheltonozhskii, AM Bronstein, A Mendelson
2018 IEEE International Parallel and Distributed Processing Symposium …, 2018
Starcoder 2 and the stack v2: The next generation
A Lozhkov, R Li, LB Allal, F Cassano, J Lamy-Poirier, N Tazi, A Tang, ...
arXiv preprint arXiv:2402.19173, 2024
Feature map transform coding for energy-efficient CNN inference
B Chmiel, C Baskin, E Zheltonozhskii, R Banner, Y Yermolin, ...
2020 International Joint Conference on Neural Networks (IJCNN), 1-9, 2020
Early-stage neural network hardware performance analysis
A Karbachevsky, C Baskin, E Zheltonozhskii, Y Yermolin, F Gabbay, ...
Sustainability 13 (2), 717, 2021
Single-node attacks for fooling graph neural networks
B Finkelshtein, C Baskin, E Zheltonozhskii, U Alon
Neurocomputing 513, 1-12, 2022
CAT: Compression-Aware Training for bandwidth reduction
C Baskin, B Chmiel, E Zheltonozhskii, R Banner, AM Bronstein, ...
Journal of Machine Learning Research 22 (269), 1-20, 2021
Self-supervised learning for large-scale unsupervised image clustering
E Zheltonozhskii, C Baskin, AM Bronstein, A Mendelson
arXiv preprint arXiv:2008.10312, 2020
Adversarial robustness via noise injection in smoothed models
Y Nemcovsky, E Zheltonozhskii, C Baskin, B Chmiel, AM Bronstein, ...
Applied Intelligence 53 (8), 9483-9498, 2023
Colored noise injection for training adversarially robust neural networks
E Zheltonozhskii, C Baskin, Y Nemcovsky, B Chmiel, A Mendelson, ...
arXiv preprint arXiv:2003.02188, 2020
Towards learning of filter-level heterogeneous compression of convolutional neural networks
Y Zur, C Baskin, E Zheltonozhskii, B Chmiel, I Evron, AM Bronstein, ...
arXiv preprint arXiv:1904.09872, 2019
Semi-Supervised Semantic Segmentation via Marginal Contextual Information
M Kimhi, S Kimhi, E Zheltonozhskii, O Litany, C Baskin
arXiv preprint arXiv:2308.13900, 2023
System and method for emulating quantization noise for a neural network
C Baskin, E Schwartz, E Zheltonozhskii, A Bronstein, L Natan, ...
US Patent 11,972,347, 2024
Identifying the topological order of quantized half-filled Landau levels through their daughter states
E Zheltonozhskii, A Stern, N Lindner
arXiv preprint arXiv:2405.03780, 2024
The system can't perform the operation now. Try again later.
Articles 1–20