Itay Hubara

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Minimum Variance Unbiased N: M Sparsity for the Neural Gradients.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Optimal Fine-Grained N: M sparsity for Activations and Neural Gradients.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N: M Transposable Masks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Accurate Post Training Quantization With Small Calibration Sets.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming.

[BibT_eX]

[DOI]

CoRR, 2020

MLPerf Inference Benchmark.

[BibT_eX]

[DOI]

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

Augment Your Batch: Improving Generalization Through Instance Repetition.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

The Knowledge Within: Methods for Data-Free Model Compression.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Mix & Match: training convnets with mixed image sizes for improved accuracy, speed and scale resiliency.

[BibT_eX]

[DOI]

CoRR, 2019

Augment your batch: better training with larger batches.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Scalable methods for 8-bit training of neural networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Fix your classifier: the marginal value of training the last weight layer.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

Train longer, generalize better: closing the generalization gap in large batch training of neural networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Playing SNES in the Retro Learning Environment.

[BibT_eX]

[DOI]

Nadav Bhonker

Shai Rozenberg

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Spatial contrasting for deep unsupervised learning.

[BibT_eX]

[DOI]

Nir Ailon

CoRR, 2016

Deep unsupervised learning through spatial contrasting.

[BibT_eX]

[DOI]

Nir Ailon

CoRR, 2016

Binarized Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2014

Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights.

[BibT_eX]

[DOI]