activity
20162026
most citedBinarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

2.2k citations · 5.3k across the 18 of their papers we have counts for

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Showing 2024Show all

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cs.LG2024

Foldable SuperNets: Scalable Merging of Transformers with Different Initializations and Tasks

Edan Kinderman, Itay Hubara, Haggai Maron +1

Recent methods aim to merge neural networks (NNs) with identical architectures trained on different tasks into a single multi-task model. While most works focus on the simpler setu…

cs.LG2024

Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators

Yaniv Blumenfeld, Itay Hubara, Daniel Soudry

The majority of the research on the quantization of Deep Neural Networks (DNNs) is focused on reducing the precision of tensors visible by high-level frameworks (e.g., weights, act…