18 citations · 52 across the 13 of their papers we have counts for
4 papers · 1 filter
Random Search Hyper-Parameter Tuning: Expected Improvement Estimation and the Corresponding Lower Bound
Dan Navon, Alex M. Bronstein
Hyperparameter tuning is a common technique for improving the performance of neural networks. Most techniques for hyperparameter search involve an iterated process where the model…
Transformer Vs. MLP-Mixer: Exponential Expressive Gap For NLP Problems
Dan Navon, Alex M. Bronstein
Vision-Transformers are widely used in various vision tasks. Meanwhile, there is another line of works starting with the MLP-mixer trying to achieve similar performance using mlp-b…
Threat Model-Agnostic Adversarial Defense using Diffusion Models
Tsachi Blau, Roy Ganz, Bahjat Kawar +2
Deep Neural Networks (DNNs) are highly sensitive to imperceptible malicious perturbations, known as adversarial attacks. Following the discovery of this vulnerability in real-world…
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems
Yaniv Nemcovsky, Matan Jacoby, Alex M. Bronstein +1
Deep neural networks are known to be susceptible to adversarial perturbations -- small perturbations that alter the output of the network and exist under strict norm limitations. W…