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ORCIDRon Banner
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- affiliation: Hewlett Packard Enterprise Labs, Haifa, Israel
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2020 – today
- 2024
[i19]Maxim Fishman, Brian Chmiel, Ron Banner, Daniel Soudry:
Scaling FP8 training to trillion-token LLMs. CoRR abs/2409.12517 (2024)- [i18]Moran Shkolnik, Maxim Fishman, Brian Chmiel, Hilla Ben-Yaacov, Ron Banner, Kfir Yehuda Levy:
EXAQ: Exponent Aware Quantization For LLMs Acceleration. CoRR abs/2410.03185 (2024) - 2023
- [c23]Brian Chmiel, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Daniel Soudry:
Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats. ICLR 2023 - [c22]Brian Chmiel, Itay Hubara, Ron Banner, Daniel Soudry:
Minimum Variance Unbiased N: M Sparsity for the Neural Gradients. ICLR 2023 - [c21]Niv Giladi, Shahar Gottlieb, Moran Shkolnik, Asaf Karnieli, Ron Banner, Elad Hoffer, Kfir Y. Levy, Daniel Soudry:
DropCompute: simple and more robust distributed synchronous training via compute variance reduction. NeurIPS 2023 - [i17]Niv Giladi, Shahar Gottlieb, Moran Shkolnik, Asaf Karnieli, Ron Banner, Elad Hoffer, Kfir Yehuda Levy, Daniel Soudry:
DropCompute: simple and more robust distributed synchronous training via compute variance reduction. CoRR abs/2306.10598 (2023) - 2022
- [c20]Nurit Spingarn-Eliezer
, Ron Banner, Hilla Ben-Yaacov, Elad Hoffer, Tomer Michaeli:
Power Awareness in Low Precision Neural Networks. ECCV Workshops (7) 2022: 67-83 - [i16]Maxim Fishman, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Avi Mendelson:
On Recoverability of Graph Neural Network Representations. CoRR abs/2201.12843 (2022) - [i15]Nurit Spingarn-Eliezer, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Tomer Michaeli:
Energy awareness in low precision neural networks. CoRR abs/2202.02783 (2022) - [i14]Brian Chmiel, Itay Hubara, Ron Banner, Daniel Soudry:
Optimal Fine-Grained N: M sparsity for Activations and Neural Gradients. CoRR abs/2203.10991 (2022) - 2021
- [j5]Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson:
CAT: Compression-Aware Training for bandwidth reduction. J. Mach. Learn. Res. 22: 269:1-269:20 (2021) - [j4]Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson:
Loss aware post-training quantization. Mach. Learn. 110(11): 3245-3262 (2021) - [c19]Brian Chmiel, Liad Ben-Uri, Moran Shkolnik, Elad Hoffer, Ron Banner, Daniel Soudry:
Neural gradients are near-lognormal: improved quantized and sparse training. ICLR 2021 - [c18]Nurit Spingarn, Ron Banner, Tomer Michaeli:
GAN "Steerability" without optimization. ICLR 2021 - [c17]Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry:
Accurate Post Training Quantization With Small Calibration Sets. ICML 2021: 4466-4475 - [c16]Itay Hubara, Brian Chmiel, Moshe Island, Ron Banner, Joseph Naor, Daniel Soudry:
Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N: M Transposable Masks. NeurIPS 2021: 21099-21111 - [i13]Itay Hubara, Brian Chmiel, Moshe Island, Ron Banner, Seffi Naor, Daniel Soudry:
Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N: M Transposable Masks. CoRR abs/2102.08124 (2021) - [i12]Brian Chmiel, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Daniel Soudry:
Logarithmic Unbiased Quantization: Practical 4-bit Training in Deep Learning. CoRR abs/2112.10769 (2021) - 2020
- [c15]Gil Shomron, Ron Banner, Moran Shkolnik, Uri C. Weiser:
Thanks for Nothing: Predicting Zero-Valued Activations with Lightweight Convolutional Neural Networks. ECCV (10) 2020: 234-250 - [c14]Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Yevgeny Yermolin, Alex Karbachevsky, Alex M. Bronstein, Avi Mendelson:
Feature Map Transform Coding for Energy-Efficient CNN Inference. IJCNN 2020: 1-9 - [c13]Moran Shkolnik, Brian Chmiel, Ron Banner, Gil Shomron, Yury Nahshan, Alex M. Bronstein, Uri C. Weiser:
Robust Quantization: One Model to Rule Them All. NeurIPS 2020 - [i11]Moran Shkolnik, Brian Chmiel, Ron Banner, Gil Shomron, Yury Nahshan, Alexander M. Bronstein, Uri C. Weiser:
Robust Quantization: One Model to Rule Them All. CoRR abs/2002.07686 (2020) - [i10]Brian Chmiel, Liad Ben-Uri, Moran Shkolnik, Elad Hoffer, Ron Banner, Daniel Soudry:
Neural gradients are lognormally distributed: understanding sparse and quantized training. CoRR abs/2006.08173 (2020) - [i9]Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry:
Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming. CoRR abs/2006.10518 (2020) - [i8]Nurit Spingarn-Eliezer, Ron Banner, Tomer Michaeli:
GAN Steerability without optimization. CoRR abs/2012.05328 (2020)
2010 – 2019
- 2019
- [c12]Ron Banner, Yury Nahshan, Daniel Soudry:
Post training 4-bit quantization of convolutional networks for rapid-deployment. NeurIPS 2019: 7948-7956 - [i7]Brian Chmiel, Chaim Baskin, Ron Banner, Evgenii Zheltonozhskii, Yevgeny Yermolin, Alex Karbachevsky, Alexander M. Bronstein, Avi Mendelson:
Feature Map Transform Coding for Energy-Efficient CNN Inference. CoRR abs/1905.10830 (2019) - [i6]Gil Shomron, Ron Banner, Moran Shkolnik, Uri C. Weiser:
Thanks for Nothing: Predicting Zero-Valued Activations with Lightweight Convolutional Neural Networks. CoRR abs/1909.07636 (2019) - [i5]Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii, Ron Banner, Alexander M. Bronstein, Avi Mendelson:
CAT: Compression-Aware Training for bandwidth reduction. CoRR abs/1909.11481 (2019) - [i4]Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alexander M. Bronstein, Avi Mendelson:
Loss Aware Post-training Quantization. CoRR abs/1911.07190 (2019) - 2018
- [c11]Elad Hoffer, Ron Banner, Itay Golan, Daniel Soudry:
Norm matters: efficient and accurate normalization schemes in deep networks. NeurIPS 2018: 2164-2174 - [c10]Ron Banner, Itay Hubara, Elad Hoffer, Daniel Soudry:
Scalable methods for 8-bit training of neural networks. NeurIPS 2018: 5151-5159 - [i3]Elad Hoffer, Ron Banner, Itay Golan, Daniel Soudry:
Norm matters: efficient and accurate normalization schemes in deep networks. CoRR abs/1803.01814 (2018) - [i2]Ron Banner, Itay Hubara, Elad Hoffer, Daniel Soudry:
Scalable Methods for 8-bit Training of Neural Networks. CoRR abs/1805.11046 (2018) - [i1]Ron Banner, Yury Nahshan, Elad Hoffer, Daniel Soudry:
ACIQ: Analytical Clipping for Integer Quantization of neural networks. CoRR abs/1810.05723 (2018) - 2013
- [c9]Fabiane Queiroz, Tsang Ing Ren, Lior Shapira, Ron Banner:
Image deblurring using maps of highlights. ICASSP 2013: 1608-1611 - 2011
- [c8]Ron Banner:
What makes good image composition? Human Vision and Electronic Imaging 2011: 786505 - [c7]Ron Banner, Omer Barkol, Ruth Bergman, Shahar Golan, Yuval Carmel, Ido Ish-Hurwitz, Oded Zilinsky:
Automatic Policy Rule Extraction for Configuration Management. POLICY 2011: 125-128 - 2010
- [c6]Michal Aharon, Ira Cohen, Arik Itskovitch, Inbal Marhaim, Ron Banner:
The PARIS Algorithm for Determining Latent Topics. ICDM Workshops 2010: 1092-1099 - [c5]Ron Banner, Ariel Orda:
Designing Low-Capacity Backup Networks for Fast Restoration. INFOCOM 2010: 1864-1872
2000 – 2009
- 2008
- [c4]Ron Banner, Ariel Orda:
Multi-Objective Topology Control in Wireless Networks. INFOCOM 2008: 448-456 - 2007
- [j3]Ron Banner, Ariel Orda:
Bottleneck Routing Games in Communication Networks. IEEE J. Sel. Areas Commun. 25(6): 1173-1179 (2007) - [j2]Ron Banner, Ariel Orda:
Multipath routing algorithms for congestion minimization. IEEE/ACM Trans. Netw. 15(2): 413-424 (2007) - [j1]Ron Banner, Ariel Orda:
The power of tuning: a novel approach for the efficient design of survivable networks. IEEE/ACM Trans. Netw. 15(4): 737-749 (2007) - 2006
- [c3]Ron Banner, Ariel Orda:
Bottleneck Routing Games in Communication Networks. INFOCOM 2006 - 2005
- [c2]Ron Banner, Ariel Orda:
Multipath Routing Algorithms for Congestion Minimization. NETWORKING 2005: 536-548 - 2004
- [c1]Ron Banner, Ariel Orda:
The Power of Tuning: A Novel Approach for the Efficient Design of Survivable Networks. ICNP 2004: 2-11
Coauthor Index
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