Search Results for author: Guy Moshkowich

Found 6 papers, 0 papers with code

A methodology for training homomorphicencryption friendly neural networks

no code implementations5 Nov 2021 Moran Baruch, Nir Drucker, Lev Greenberg, Guy Moshkowich

Experiments using our approach reduced the gap between the F1 score and accuracy of the models trained with ReLU and the HE-friendly model to within a mere 0. 32-5. 3 percent degradation.

Knowledge Distillation Privacy Preserving

Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains

no code implementations Findings of the Association for Computational Linguistics 2020 Eyal Shnarch, Leshem Choshen, Guy Moshkowich, Noam Slonim, Ranit Aharonov

Approaching new data can be quite deterrent; you do not know how your categories of interest are realized in it, commonly, there is no labeled data at hand, and the performance of domain adaptation methods is unsatisfactory.

Domain Adaptation

Argument Invention from First Principles

no code implementations ACL 2019 Yonatan Bilu, Ariel Gera, Daniel Hershcovich, Benjamin Sznajder, Dan Lahav, Guy Moshkowich, Anael Malet, Assaf Gavron, Noam Slonim

In this work we aim to explicitly define a taxonomy of such principled recurring arguments, and, given a controversial topic, to automatically identify which of these arguments are relevant to the topic.

Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network

no code implementations ACL 2019 Martin Gleize, Eyal Shnarch, Leshem Choshen, Lena Dankin, Guy Moshkowich, Ranit Aharonov, Noam Slonim

With the advancement in argument detection, we suggest to pay more attention to the challenging task of identifying the more convincing arguments.

Cannot find the paper you are looking for? You can Submit a new open access paper.