--- title: "Itay Hubara — author profile and papers — Elamur Research" description: "Itay Hubara: 2 papers on Elamur Research (2016), h-index 14 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/itay-hubara/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/itay-hubara/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Itay Hubara # Itay Hubara Itay Hubara has 2 papers in our library, in 2016, most of them on [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Daniel Soudry](https://md.research.elamur.ai/free/en/authors/daniel-soudry/), [Matthieu Courbariaux](https://md.research.elamur.ai/free/en/authors/matthieu-courbariaux/), [Ran El-Yaniv](https://md.research.elamur.ai/free/en/authors/ran-el-yaniv/). 2 papers in our library · 2016 [OpenAlex](https://openalex.org/A5087518651) · [**h-index 14**](https://openalex.org/authors/A5087518651) · [34 works](https://openalex.org/works?filter=author.id:A5087518651) · [6,181 citations](https://openalex.org/works?filter=author.id:A5087518651&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/itay-hubara/#papers) · [🔗 Cited 251 times in our library](https://md.research.elamur.ai/free/en/authors/itay-hubara/cited-by/) · [⭐ Paper Stars ranking: #930](https://md.research.elamur.ai/free/en/paper-stars/page/10/#star-930) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Itay+Hubara) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Itay+Hubara) · [dblp](https://dblp.org/search?q=Itay+Hubara) · [ACL Anthology](https://aclanthology.org/search/?q=Itay+Hubara) ## Affiliations [🎓**Technion – Israel Institute of Technology** Haifa · Israel 2014–2024 · 14 papers](https://md.research.elamur.ai/free/en/universities/technion-israel-institute-of-technology/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 5 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Engineering · 2 works](https://md.research.elamur.ai/free/en/shelves/engineering/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Electrical and Electronic Engineering · 2 works](https://md.research.elamur.ai/free/en/shelves/engineering/electrical-and-electronic-engineering/) · [Artificial Intelligence · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) 🧭 Topics 1 Research subjects and languages the work is about.[Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) ## Works by year ### 2010s [**2016** 2 papers](https://md.research.elamur.ai/free/en/authors/itay-hubara/year/2016/) ## Papers The most cited first (OpenAlex and our library). 1. **[Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1](https://md.research.elamur.ai/free/en/papers/courbariaux-2016-binarized-neural-networks-training-deep/)** *(2016 · 2,143 citations)* This work tackles the cost of running deep networks on low-power hardware. Modern DNNs depend on energy-hungry GPUs and full-precision arithmetic. The authors propose Binarized Neural Networks (BNNs), in which weights and hidden activations take only the values +1 or −1. These binary values are used both at inference… 2. **[Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations](https://md.research.elamur.ai/free/en/papers/hubara-2016-quantized-neural-networks-training-neural/)** *(2016 · 1,610 citations)* The paper tackles the high cost of running deep networks, whose many multiply-accumulate operations make them slow and power-hungry on ordinary hardware and low-power devices. ## Co-authors here 4 co-authors with a page, the most papers together first. - [Daniel Soudry](https://md.research.elamur.ai/free/en/authors/daniel-soudry/) ×2 - [Matthieu Courbariaux](https://md.research.elamur.ai/free/en/authors/matthieu-courbariaux/) ×2 - [Ran El-Yaniv](https://md.research.elamur.ai/free/en/authors/ran-el-yaniv/) ×2 - [Yoshua Bengio](https://md.research.elamur.ai/free/en/authors/yoshua-bengio/) ×2 ## Cited by Papers of our library cite their works 251 times (of the 149,439 papers whose bibliographies we read); [18 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/itay-hubara/cited-by/). Updated 2 November 2026