Elad Hoffer

1.8k citations
10 papers · 256 indexed · h-index 5

Impact in

Papers in

    • Domain Adaptation and Few-Shot Learning 6
    • Neural Networks and Applications 3
    • Adversarial Robustness in Machine Learning 2
    • Advanced Neural Network Applications 4
    • Video Surveillance and Tracking Methods 1
    • Face and Expression Recognition 1
    • Multimodal Machine Learning Applications 1
Journals
arXiv (Cornell University) (6 papers)Neural Information Processing Systems (2 papers)Repository for Publications and Research Data (ETH Zurich) (1 paper)

In The Last Decade

Elad Hoffer

10 papers receiving 245 citations

Peers

Elad Hoffer
Comparison fields: 5 of 52
  • Computational Mathematics 7
  • Computer Vision and Pattern Recognition 183
  • Artificial Intelligence 152
  • Media Technology 14
  • Hardware and Architecture 7
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Citations per field
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Citations per year

Countries citing papers authored by Elad Hoffer

Since Specialization
Citations

This map shows the geographic impact of Elad Hoffer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Elad Hoffer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Elad Hoffer more than expected).

Fields of papers citing papers by Elad Hoffer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Elad Hoffer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Elad Hoffer. The network helps show where Elad Hoffer may publish in the future.

Co-authors

The 8 scholars most cited alongside Elad Hoffer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Elad Hoffer Line = papers co-authored together Elad Hoffer links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 202090
2
Scalable methods for 8-bit training of neural networks
201852
3
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
201748
4
ACIQ: Analytical Clipping for Integer Quantization of neural networks
201840
5
Norm matters: efficient and accurate normalization schemes in deep networks
201816
6
Quantized Back-Propagation: Training Binarized Neural Networks with Quantized Gradients
20184
7
Semi-supervised deep learning by metric embedding
20173
8
Bayesian Gradient Descent: Online Variational Bayes Learning with Increased Robustness to Catastrophic Forgetting and Weight Pruning.
20181
9
At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks?
20201
10
Neural gradients are lognormally distributed: understanding sparse and quantized training.
20201

About Elad Hoffer

Elad Hoffer is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Computational Mechanics and Computational Theory and Mathematics, having authored 10 papers that have together received 256 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (6 papers), Advanced Neural Network Applications (4 papers), Neural Networks and Applications (3 papers), Model Reduction and Neural Networks (2 papers), Adversarial Robustness in Machine Learning (2 papers), Video Surveillance and Tracking Methods (1 paper), Face and Expression Recognition (1 paper) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Computational Mathematics (7 citations), Computer Vision and Pattern Recognition (183 citations), Artificial Intelligence (152 citations), Media Technology (14 citations) and Hardware and Architecture (7 citations). Elad Hoffer has collaborated with scholars based in Israel, United States and Switzerland. Frequent co-authors include Daniel Soudry, Itay Hubara, Ron Banner, Tal Ben‐Nun, Torsten Hoefler, Niv Giladi, Yury Nahshan and Nir Ailon. Their work appears in journals such as arXiv (Cornell University), Neural Information Processing Systems and Repository for Publications and Research Data (ETH Zurich).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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