Elad Hoffer

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 36

Top Topics

Multilayer Neural Networks

Top Venues

ICLR (Workshop)

Publications

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 (2023)
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)
Brian Chmiel, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Daniel Soudry
Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats. ICLR (2023)
Nurit Spingarn-Eliezer, Ron Banner, Hilla Ben-Yaacov, Elad Hoffer, Tomer Michaeli
Power Awareness in Low Precision Neural Networks. ECCV Workshops (7) (2022)
Nurit Spingarn-Eliezer, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Tomer Michaeli
Energy awareness in low precision neural networks. CoRR (2022)
Chen Zeno, Itay Golan, Elad Hoffer, Daniel Soudry
Task-Agnostic Continual Learning Using Online Variational Bayes With Fixed-Point Updates. Neural Comput. 33 (11) (2021)
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)
Brian Chmiel, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Daniel Soudry
Logarithmic Unbiased Quantization: Practical 4-bit Training in Deep Learning. CoRR (2021)
Matan Haroush, Itay Hubara, Elad Hoffer, Daniel Soudry
The Knowledge Within: Methods for Data-Free Model Compression. CVPR (2020)
Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, Daniel Soudry
Augment Your Batch: Improving Generalization Through Instance Repetition. CVPR (2020)
Chen Zeno, Itay Golan, Elad Hoffer, Daniel Soudry
Task Agnostic Continual Learning Using Online Variational Bayes with Fixed-Point Updates. CoRR (2020)
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)
Brian Chmiel, Liad Ben-Uri, Moran Shkolnik, Elad Hoffer, Ron Banner, Daniel Soudry
Neural gradients are lognormally distributed: understanding sparse and quantized training. CoRR (2020)
Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, Daniel Soudry
Augment your batch: better training with larger batches. CoRR (2019)
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 (2019)
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 (2019)
Matan Haroush, Itay Hubara, Elad Hoffer, Daniel Soudry
The Knowledge Within: Methods for Data-Free Model Compression. CoRR (2019)
Ron Banner, Itay Hubara, Elad Hoffer, Daniel Soudry
Scalable methods for 8-bit training of neural networks. NeurIPS (2018)
Ron Banner, Yury Nahshan, Elad Hoffer, Daniel Soudry
ACIQ: Analytical Clipping for Integer Quantization of neural networks. CoRR (2018)
Daniel Soudry, Elad Hoffer
Exponentially vanishing sub-optimal local minima in multilayer neural networks. ICLR (Workshop) (2018)
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 (2018)
Elad Hoffer, Ron Banner, Itay Golan, Daniel Soudry
Norm matters: efficient and accurate normalization schemes in deep networks. CoRR (2018)
Elad Hoffer, Ron Banner, Itay Golan, Daniel Soudry
Norm matters: efficient and accurate normalization schemes in deep networks. NeurIPS (2018)
Ron Banner, Itay Hubara, Elad Hoffer, Daniel Soudry
Scalable Methods for 8-bit Training of Neural Networks. CoRR (2018)
Daniel Soudry, Elad Hoffer, Mor Shpigel Nacson, Nathan Srebro
The Implicit Bias of Gradient Descent on Separable Data. ICLR (Poster) (2018)
Elad Hoffer, Itay Hubara, Daniel Soudry
Fix your classifier: the marginal value of training the last weight layer. ICLR (Poster) (2018)
Elad Hoffer, Itay Hubara, Daniel Soudry
Fix your classifier: the marginal value of training the last weight layer. CoRR (2018)
Elad Hoffer, Shai Fine, Daniel Soudry
On the Blindspots of Convolutional Networks. CoRR (2018)
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 (2018)
Elad Hoffer, Nir Ailon
Semi-supervised deep learning by metric embedding. ICLR (Workshop) (2017)
Daniel Soudry, Elad Hoffer, Nathan Srebro
The Implicit Bias of Gradient Descent on Separable Data. CoRR (2017)
Elad Hoffer, Itay Hubara, Daniel Soudry
Train longer, generalize better: closing the generalization gap in large batch training of neural networks. CoRR (2017)
Elad Hoffer, Itay Hubara, Daniel Soudry
Train longer, generalize better: closing the generalization gap in large batch training of neural networks. NIPS (2017)
Elad Hoffer, Nir Ailon
Semi-supervised deep learning by metric embedding. CoRR (2016)
Elad Hoffer, Itay Hubara, Nir Ailon
Spatial contrasting for deep unsupervised learning. CoRR (2016)
Elad Hoffer, Itay Hubara, Nir Ailon
Deep unsupervised learning through spatial contrasting. CoRR (2016)
Elad Hoffer, Nir Ailon
Deep metric learning using Triplet network. ICLR (Workshop) (2015)
Elad Hoffer, Nir Ailon
Deep Metric Learning Using Triplet Network. SIMBAD (2015)