Ron Banner

1.5k citations
18 papers · 535 · h-index 10

Impact in

Papers in

Ron Banner

17 papers receiving 510 citations

Peers

Ron Banner
Comparison fields: 5 of 60
  • Computational Mathematics 10
  • Computer Vision and Pattern Recognition 244
  • Computer Networks and Communications 209
  • Artificial Intelligence 171
  • Hardware and Architecture 28
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Citations per field
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Citations per year

Countries citing papers authored by Ron Banner

Since Specialization
Citations

This map shows the geographic impact of Ron Banner'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 Ron Banner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ron Banner more than expected).

Fields of papers citing papers by Ron Banner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ron Banner. 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 Ron Banner. The network helps show where Ron Banner may publish in the future.

Co-authors

The 9 scholars most cited alongside Ron Banner, 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 Ron Banner Line = papers co-authored together Ron Banner links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1
Post training 4-bit quantization of convolutional networks for rapid-deployment
2019175
2 2007102
3
Scalable methods for 8-bit training of neural networks
201852
4 200747
5
ACIQ: Analytical Clipping for Integer Quantization of neural networks
201840
6 201024
7
Accurate Post Training Quantization With Small Calibration Sets
202120
8 200717
9
Norm matters: efficient and accurate normalization schemes in deep networks
201816
10 200816
11 20069
12 20045
13 20135
14
Bottleneck games in noncooperative networks
20043
15 20082
16
Neural gradients are lognormally distributed: understanding sparse and quantized training.
20201
17 20111
18 20110

About Ron Banner

Ron Banner is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Statistical and Nonlinear Physics, Artificial Intelligence and Electrical and Electronic Engineering, having authored 18 papers that have together received 535 indexed citations. Recurring topics across this work include Advanced Optical Network Technologies (4 papers), Advanced Neural Network Applications (4 papers), Software-Defined Networks and 5G (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Game Theory and Applications (2 papers), Network Traffic and Congestion Control (2 papers), Mobile Ad Hoc Networks (2 papers) and Complex Network Analysis Techniques (2 papers). The work is most often cited by research in Computational Mathematics (10 citations), Computer Vision and Pattern Recognition (244 citations), Computer Networks and Communications (209 citations), Artificial Intelligence (171 citations) and Hardware and Architecture (28 citations). Ron Banner has collaborated with scholars based in Israel, United States and Brazil. Frequent co-authors include Ariel Orda, Daniel Soudry, Yury Nahshan, Elad Hoffer, Itay Hubara, Yair Hanani, Lior Shapira, Tsang Ing Ren and Y. Carmel. Their work appears in journals such as IEEE/ACM Transactions on Networking, IEEE Journal on Selected Areas in Communications, 2008 Proceedings IEEE INFOCOM - The 27th Conference on Computer Communications, arXiv (Cornell University) and Neural Information Processing Systems.

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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