1 code implementation • 24 Oct 2021 • Niv Nayman, Yonathan Aflalo, Asaf Noy, Rong Jin, Lihi Zelnik-Manor
Practical use of neural networks often involves requirements on latency, energy and memory among others.
2 code implementations • 23 Feb 2021 • Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik-Manor
Realistic use of neural networks often requires adhering to multiple constraints on latency, energy and memory among others.
Ranked #21 on Neural Architecture Search on ImageNet
no code implementations • 12 Jan 2021 • Asaf Noy, Yi Xu, Yonathan Aflalo, Lihi Zelnik-Manor, Rong Jin
We show that convergence to a global minimum is guaranteed for networks with widths quadratic in the sample size and linear in their depth at a time logarithmic in both.
1 code implementation • 19 Feb 2020 • Yonathan Aflalo, Asaf Noy, Ming Lin, Itamar Friedman, Lihi Zelnik
Through this we produce compact architectures with the same FLOPs as EfficientNet-B0 and MobileNetV3 but with higher accuracy, by $1\%$ and $0. 3\%$ respectively on ImageNet, and faster runtime on GPU.
Ranked #3 on Network Pruning on ImageNet
no code implementations • ICCV 2015 • Gil Shamai, Yonathan Aflalo, Michael Zibulevsky, Ron Kimmel
We present an efficient solver for Classical Scaling (a specific MDS model) by extending the distances measured from a subset of the points to the rest, while exploiting the smoothness property of the distance functions.
no code implementations • 15 Sep 2014 • Yonathan Aflalo, Haim Brezis, Ron Kimmel
This novel pseudo-metric allows constructing an LBO by which a scale invariant eigenspace on the surface is defined.
no code implementations • 29 Jan 2014 • Yonathan Aflalo, Alex Bronstein, Ron Kimmel
We consider the problem of exact and inexact matching of weighted undirected graphs, in which a bijective correspondence is sought to minimize a quadratic weight disagreement.