164 citations · 430 across the 25 of their papers we have counts for
8 papers · 1 filter
THOR: Threshold-Based Ranking Loss for Ordinal Regression
Tzeviya Sylvia Fuchs, Joseph Keshet
In this work, we present a regression-based ordinal regression algorithm for supervised classification of instances into ordinal categories. In contrast to previous methods, in thi…
Constant Random Perturbations Provide Adversarial Robustness with Minimal Effect on Accuracy
Bronya Roni Chernyak, Bhiksha Raj, Tamir Hazan +1
This paper proposes an attack-independent (non-adversarial training) technique for improving adversarial robustness of neural network models, with minimal loss of standard accuracy…
Redesigning the classification layer by randomizing the class representation vectors
Gabi Shalev, Gal-Lev Shalev, Joseph Keshet
Neural image classification models typically consist of two components. The first is an image encoder, which is responsible for encoding a given raw image into a representative vec…
Fooling End-to-end Speaker Verification by Adversarial Examples
Felix Kreuk, Yossi Adi, Moustapha Cisse +1
Automatic speaker verification systems are increasingly used as the primary means to authenticate costumers. Recently, it has been proposed to train speaker verification systems us…
Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring
Yossi Adi, Carsten Baum, Moustapha Cisse +2
Deep Neural Networks have recently gained lots of success after enabling several breakthroughs in notoriously challenging problems. Training these networks is computationally expen…
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Felix Kreuk, Assi Barak, Shir Aviv-Reuven +3
In recent years, deep learning has shown performance breakthroughs in many applications, such as image detection, image segmentation, pose estimation, and speech recognition. Howev…
Context-Based Prediction of App Usage
Joseph Keshet, Adam Kariv, Arnon Dagan +2
There are around a hundred installed apps on an average smartphone. The high number of apps and the limited number of app icons that can be displayed on the device's screen require…
Risk Minimization in Structured Prediction using Orbit Loss
Danny Karmon, Joseph Keshet
We introduce a new surrogate loss function called orbit loss in the structured prediction framework, which has good theoretical and practical advantages. While the orbit loss is no…