Bottleneck Routing Games in Communication Networks. - Ron Banner; Ariel Orda (IEEE J. Sel. Areas Commun., 2007)

Multipath routing algorithms for congestion minimization. - Ron Banner; Ariel Orda (IEEE/ACM Trans. Netw., 2007)

The power of tuning: a novel approach for the efficient design of survivable networks. - Ron Banner; Ariel Orda (IEEE/ACM Trans. Netw., 2007)

Multi-Objective Topology Control in Wireless Networks. - Ron Banner; Ariel Orda (INFOCOM, 2008)

The PARIS Algorithm for Determining Latent Topics. - Michal Aharon; Ira Cohen; Arik Itskovitch; Inbal Marhaim; Ron Banner (ICDM Workshops, 2010)

Designing Low-Capacity Backup Networks for Fast Restoration. - Ron Banner; Ariel Orda (INFOCOM, 2010)

What makes good image composition? - Ron Banner (Human Vision and Electronic Imaging, 2011)

Automatic Policy Rule Extraction for Configuration Management. - Ron Banner; Omer Barkol; Ruth Bergman; Shahar Golan; Yuval Carmel; Ido Ish-Hurwitz; Oded Zilinsky (POLICY, 2011)

Image deblurring using maps of highlights. - Fabiane Queiroz; Tsang Ing Ren; Lior Shapira; Ron Banner (ICASSP, 2013)

Scalable methods for 8-bit training of neural networks. - Ron Banner; Itay Hubara; Elad Hoffer; Daniel Soudry (NeurIPS, 2018)

Norm matters: efficient and accurate normalization schemes in deep networks. - Elad Hoffer; Ron Banner; Itay Golan; Daniel Soudry (NeurIPS, 2018)

ACIQ: Analytical Clipping for Integer Quantization of neural networks. - Ron Banner; Yury Nahshan; Elad Hoffer; Daniel Soudry (CoRR, 2018)

Post training 4-bit quantization of convolutional networks for rapid-deployment. - Ron Banner; Yury Nahshan; Daniel Soudry (NeurIPS, 2019)

Thanks for Nothing: Predicting Zero-Valued Activations with Lightweight Convolutional Neural Networks. - Gil Shomron; Ron Banner; Moran Shkolnik; Uri C. Weiser (ECCV (10), 2020)

Feature Map Transform Coding for Energy-Efficient CNN Inference. - Brian Chmiel; Chaim Baskin; Evgenii Zheltonozhskii; Ron Banner; Yevgeny Yermolin; Alex Karbachevsky; Alex M. Bronstein; Avi Mendelson (IJCNN, 2020)

Robust Quantization: One Model to Rule Them All. - Moran Shkolnik; Brian Chmiel; Ron Banner; Gil Shomron; Yury Nahshan; Alex M. Bronstein; Uri C. Weiser (NeurIPS, 2020)

Neural gradients are lognormally distributed: understanding sparse and quantized training. - Brian Chmiel; Liad Ben-Uri; Moran Shkolnik; Elad Hoffer; Ron Banner; Daniel Soudry (CoRR, 2020)

Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming. - Itay Hubara; Yury Nahshan; Yair Hanani; Ron Banner; Daniel Soudry (CoRR, 2020)

Neural gradients are near-lognormal: improved quantized and sparse training. - Brian Chmiel; Liad Ben-Uri; Moran Shkolnik; Elad Hoffer; Ron Banner; Daniel Soudry (ICLR, 2021)

GAN "Steerability" without optimization. - Nurit Spingarn; Ron Banner; Tomer Michaeli (ICLR, 2021)

Accurate Post Training Quantization With Small Calibration Sets. - Itay Hubara; Yury Nahshan; Yair Hanani; Ron Banner; Daniel Soudry (ICML, 2021)

Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N: M Transposable Masks. - Itay Hubara; Brian Chmiel; Moshe Island; Ron Banner; Joseph Naor; Daniel Soudry (NeurIPS, 2021)

Logarithmic Unbiased Quantization: Practical 4-bit Training in Deep Learning. - Brian Chmiel; Ron Banner; Elad Hoffer; Hilla Ben-Yaacov; Daniel Soudry (CoRR, 2021)

CAT: Compression-Aware Training for bandwidth reduction. - Chaim Baskin; Brian Chmiel; Evgenii Zheltonozhskii; Ron Banner; Alex M. Bronstein; Avi Mendelson (J. Mach. Learn. Res., 2021)

Loss aware post-training quantization. - Yury Nahshan; Brian Chmiel; Chaim Baskin; Evgenii Zheltonozhskii; Ron Banner; Alex M. Bronstein; Avi Mendelson (Mach. Learn., 2021)

Power Awareness in Low Precision Neural Networks. - Nurit Spingarn-Eliezer; Ron Banner; Hilla Ben-Yaacov; Elad Hoffer; Tomer Michaeli (ECCV Workshops (7), 2022)

On Recoverability of Graph Neural Network Representations. - Maxim Fishman; Chaim Baskin; Evgenii Zheltonozhskii; Ron Banner; Avi Mendelson (CoRR, 2022)

Energy awareness in low precision neural networks. - Nurit Spingarn-Eliezer; Ron Banner; Elad Hoffer; Hilla Ben-Yaacov; Tomer Michaeli (CoRR, 2022)

Optimal Fine-Grained N: M sparsity for Activations and Neural Gradients. - Brian Chmiel; Itay Hubara; Ron Banner; Daniel Soudry (CoRR, 2022)

Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats. - Brian Chmiel; Ron Banner; Elad Hoffer; Hilla Ben-Yaacov; Daniel Soudry (ICLR, 2023)

Minimum Variance Unbiased N: M Sparsity for the Neural Gradients. - Brian Chmiel; Itay Hubara; Ron Banner; Daniel Soudry (ICLR, 2023)

DropCompute: simple and more robust distributed synchronous training via compute variance reduction. - Niv Giladi; Shahar Gottlieb; Moran Shkolnik; Asaf Karnieli; Ron Banner; Elad Hoffer; Kfir Y. Levy; Daniel Soudry (NeurIPS, 2023)

EXAQ: Exponent Aware Quantization For LLMs Acceleration. - Moran Shkolnik; Maxim Fishman; Brian Chmiel; Hilla Ben-Yaacov; Ron Banner; Kfir Yehuda Levy (CoRR, 2024)

Scaling FP8 training to trillion-token LLMs. - Maxim Fishman; Brian Chmiel; Ron Banner; Daniel Soudry (ICLR, 2025)

FP4 All the Way: Fully Quantized Training of LLMs. - Brian Chmiel; Maxim Fishman; Ron Banner; Daniel Soudry (CoRR, 2025)

Distributed Training under Packet Loss. - Erez Weintraub; Ron Banner; Ariel Orda (CoRR, 2025)