R
Ran El-Yaniv
Researcher at Technion – Israel Institute of Technology
Publications - 138
Citations - 14744
Ran El-Yaniv is an academic researcher from Technion – Israel Institute of Technology. The author has contributed to research in topics: Support vector machine & Competitive analysis. The author has an hindex of 40, co-authored 133 publications receiving 12684 citations. Previous affiliations of Ran El-Yaniv include University of Toronto & Google.
Papers
More filters
Book
Online Computation and Competitive Analysis
Allan Borodin,Ran El-Yaniv +1 more
TL;DR: This book discusses competitive analysis and decision making under uncertainty in the context of the k-server problem, which involves randomized algorithms in order to solve the problem of paging.
Posted Content
Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
TL;DR: A binary matrix multiplication GPU kernel is written with which it is possible to run the MNIST BNN 7 times faster than with an unoptimized GPU kernel, without suffering any loss in classification accuracy.
Proceedings Article
Binarized Neural Networks
TL;DR: A binary matrix multiplication GPU kernel is written with which it is possible to run the MNIST BNN 7 times faster than with an unoptimized GPU kernel, without suffering any loss in classification accuracy.
Posted Content
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations
TL;DR: A binary matrix multiplication GPU kernel is programmed with which it is possible to run the MNIST QNN 7 times faster than with an unoptimized GPU kernel, without suffering any loss in classification accuracy.
Journal Article
Quantized neural networks: training neural networks with low precision weights and activations
TL;DR: In this paper, a method to train quantized neural networks (QNNs) with extremely low precision (e.g., 1-bit) weights and activations, at run-time is introduced.