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Itay Hubara
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2020 – today
- 2024
- [c13]Yaniv Blumenfeld, Itay Hubara, Daniel Soudry:
Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators. ICLR 2024 - [i16]Yaniv Blumenfeld, Itay Hubara, Daniel Soudry:
Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators. CoRR abs/2401.14110 (2024) - [i15]Edan Kinderman, Itay Hubara, Haggai Maron, Daniel Soudry:
Foldable SuperNets: Scalable Merging of Transformers with Different Initializations and Tasks. CoRR abs/2410.01483 (2024) - 2023
- [c12]Brian Chmiel, Itay Hubara, Ron Banner, Daniel Soudry:
Minimum Variance Unbiased N: M Sparsity for the Neural Gradients. ICLR 2023 - 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
- [c11]Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry:
Accurate Post Training Quantization With Small Calibration Sets. ICML 2021: 4466-4475 - [c10]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) - 2020
- [c9]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 - [c8]Matan Haroush, Itay Hubara, Elad Hoffer, Daniel Soudry:
The Knowledge Within: Methods for Data-Free Model Compression. CVPR 2020: 8491-8499 - [c7]Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson
, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou:
MLPerf Inference Benchmark. ISCA 2020: 446-459 - [i12]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)
2010 – 2019
- 2019
- [i11]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) - [i10]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) - [i9]Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou:
MLPerf Inference Benchmark. CoRR abs/1911.02549 (2019) - [i8]Matan Haroush, Itay Hubara, Elad Hoffer, Daniel Soudry:
The Knowledge Within: Methods for Data-Free Model Compression. CoRR abs/1912.01274 (2019) - 2018
- [c6]Elad Hoffer, Itay Hubara, Daniel Soudry:
Fix your classifier: the marginal value of training the last weight layer. ICLR (Poster) 2018 - [c5]Ron Banner, Itay Hubara, Elad Hoffer, Daniel Soudry:
Scalable methods for 8-bit training of neural networks. NeurIPS 2018: 5151-5159 - [i7]Elad Hoffer, Itay Hubara, Daniel Soudry:
Fix your classifier: the marginal value of training the last weight layer. CoRR abs/1801.04540 (2018) - [i6]Ron Banner, Itay Hubara, Elad Hoffer, Daniel Soudry:
Scalable Methods for 8-bit Training of Neural Networks. CoRR abs/1805.11046 (2018) - 2017
- [j1]Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio:
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations. J. Mach. Learn. Res. 18: 187:1-187:30 (2017) - [c4]Nadav Bhonker, Shai Rozenberg, Itay Hubara:
Playing SNES in the Retro Learning Environment. 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) - 2016
- [c2]Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio:
Binarized Neural Networks. NIPS 2016: 4107-4115 - [i4]Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio:
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations. CoRR abs/1609.07061 (2016) - [i3]Elad Hoffer, Itay Hubara, Nir Ailon:
Deep unsupervised learning through spatial contrasting. CoRR abs/1610.00243 (2016) - [i2]Nadav Bhonker, Shai Rozenberg, Itay Hubara:
Playing SNES in the Retro Learning Environment. CoRR abs/1611.02205 (2016) - [i1]Elad Hoffer, Itay Hubara, Nir Ailon:
Spatial contrasting for deep unsupervised learning. CoRR abs/1611.06996 (2016) - 2014
- [c1]Daniel Soudry, Itay Hubara, Ron Meir:
Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights. NIPS 2014: 963-971
Coauthor Index
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last updated on 2024-11-11 21:27 CET by the dblp team
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