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Elad Hoffer
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2020 – today
- 2023
- [c16]Brian Chmiel, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Daniel Soudry:
Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats. ICLR 2023 - [c15]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 - [i20]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
- [c14]Nurit Spingarn-Eliezer
, Ron Banner
Power Awareness in Low Precision Neural Networks. ECCV Workshops (7) 2022: 67-83 - [i19]Nurit Spingarn-Eliezer, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Tomer Michaeli:
Energy awareness in low precision neural networks. CoRR abs/2202.02783 (2022) - 2021
- [j2]Chen Zeno, Itay Golan, Elad Hoffer, Daniel Soudry:
Task-Agnostic Continual Learning Using Online Variational Bayes With Fixed-Point Updates. Neural Comput. 33(11): 3139-3177 (2021) - [c13]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 - [i18]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
- [c12]Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, Daniel Soudry:
Augment Your Batch: Improving Generalization Through Instance Repetition. CVPR 2020: 8126-8135 - [c11]Matan Haroush, Itay Hubara, Elad Hoffer, Daniel Soudry:
The Knowledge Within: Methods for Data-Free Model Compression. CVPR 2020: 8491-8499 - [c10]Niv Giladi, Mor Shpigel Nacson, Elad Hoffer, Daniel Soudry:
At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks? ICLR 2020 - [i17]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) - [i16]Chen Zeno, Itay Golan, Elad Hoffer, Daniel Soudry:
Task Agnostic Continual Learning Using Online Variational Bayes with Fixed-Point Updates. CoRR abs/2010.00373 (2020)
2010 – 2019
- 2019
- [i15]Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, Daniel Soudry:
Augment your batch: better training with larger batches. CoRR abs/1901.09335 (2019) - [i14]Elad Hoffer, Berry Weinstein, Itay Hubara, Tal Ben-Nun, Torsten Hoefler, Daniel Soudry:
Mix & Match: training convnets with mixed image sizes for improved accuracy, speed and scale resiliency. CoRR abs/1908.08986 (2019) - [i13]Niv Giladi, Mor Shpigel Nacson, Elad Hoffer, Daniel Soudry:
At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks? CoRR abs/1909.12340 (2019) - [i12]Matan Haroush, Itay Hubara, Elad Hoffer, Daniel Soudry:
The Knowledge Within: Methods for Data-Free Model Compression. CoRR abs/1912.01274 (2019) - 2018
- [j1]Daniel Soudry, Elad Hoffer, Mor Shpigel Nacson, Suriya Gunasekar, Nathan Srebro:
The Implicit Bias of Gradient Descent on Separable Data. J. Mach. Learn. Res. 19: 70:1-70:57 (2018) - [c9]Elad Hoffer, Itay Hubara, Daniel Soudry:
Fix your classifier: the marginal value of training the last weight layer. ICLR (Poster) 2018 - [c8]Daniel Soudry, Elad Hoffer:
Exponentially vanishing sub-optimal local minima in multilayer neural networks. ICLR (Workshop) 2018 - [c7]Daniel Soudry, Elad Hoffer, Mor Shpigel Nacson, Nathan Srebro:
The Implicit Bias of Gradient Descent on Separable Data. ICLR (Poster) 2018 - [c6]Elad Hoffer, Ron Banner, Itay Golan, Daniel Soudry:
Norm matters: efficient and accurate normalization schemes in deep networks. NeurIPS 2018: 2164-2174 - [c5]Ron Banner, Itay Hubara, Elad Hoffer, Daniel Soudry:
Scalable methods for 8-bit training of neural networks. NeurIPS 2018: 5151-5159 - [i11]Elad Hoffer, Itay Hubara, Daniel Soudry:
Fix your classifier: the marginal value of training the last weight layer. CoRR abs/1801.04540 (2018) - [i10]Elad Hoffer, Shai Fine, Daniel Soudry:
On the Blindspots of Convolutional Networks. CoRR abs/1802.05187 (2018) - [i9]Elad Hoffer, Ron Banner, Itay Golan, Daniel Soudry:
Norm matters: efficient and accurate normalization schemes in deep networks. CoRR abs/1803.01814 (2018) - [i8]Chen Zeno, Itay Golan, Elad Hoffer, Daniel Soudry:
Bayesian Gradient Descent: Online Variational Bayes Learning with Increased Robustness to Catastrophic Forgetting and Weight Pruning. CoRR abs/1803.10123 (2018) - [i7]Ron Banner, Itay Hubara, Elad Hoffer, Daniel Soudry:
Scalable Methods for 8-bit Training of Neural Networks. CoRR abs/1805.11046 (2018) - [i6]Ron Banner, Yury Nahshan, Elad Hoffer, Daniel Soudry:
ACIQ: Analytical Clipping for Integer Quantization of neural networks. CoRR abs/1810.05723 (2018) - 2017
- [c4]Elad Hoffer, Nir Ailon:
Semi-supervised deep learning by metric embedding. ICLR (Workshop) 2017 - [c3]Elad Hoffer, Itay Hubara, Daniel Soudry:
Train longer, generalize better: closing the generalization gap in large batch training of neural networks. NIPS 2017: 1731-1741 - [i5]Elad Hoffer, Itay Hubara, Daniel Soudry:
Train longer, generalize better: closing the generalization gap in large batch training of neural networks. CoRR abs/1705.08741 (2017) - [i4]Daniel Soudry, Elad Hoffer, Nathan Srebro:
The Implicit Bias of Gradient Descent on Separable Data. CoRR abs/1710.10345 (2017) - 2016
- [i3]Elad Hoffer, Itay Hubara, Nir Ailon:
Deep unsupervised learning through spatial contrasting. CoRR abs/1610.00243 (2016) - [i2]Elad Hoffer, Nir Ailon:
Semi-supervised deep learning by metric embedding. CoRR abs/1611.01449 (2016) - [i1]Elad Hoffer, Itay Hubara, Nir Ailon:
Spatial contrasting for deep unsupervised learning. CoRR abs/1611.06996 (2016) - 2015
- [c2]Elad Hoffer, Nir Ailon:
Deep Metric Learning Using Triplet Network. SIMBAD 2015: 84-92 - [c1]Elad Hoffer, Nir Ailon:
Deep metric learning using Triplet network. ICLR (Workshop) 2015
Coauthor Index
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