124 citations · 126 across the 3 of their papers we have counts for
4 papers
Autoencoders
Dor Bank, Noam Koenigstein, Raja Giryes
An autoencoder is a specific type of a neural network, which is mainly designed to encode the input into a compressed and meaningful representation, and then decode it back such th…
An ETF view of Dropout regularization
Dor Bank, Raja Giryes
Dropout is a popular regularization technique in deep learning. Yet, the reason for its success is still not fully understood. This paper provides a new interpretation of Dropout f…
Reaching Distributed Equilibrium with Limited ID Space
Dor Bank, Moshe Sulamy, Eyal Waserman
We examine the relation between the size of the id space and the number of rational agents in a network under which equilibrium in distributed algorithms is possible. When the numb…
Improved Training for Self-Training by Confidence Assessments
Gal Hyams, Daniel Greenfeld, Dor Bank
It is well known that for some tasks, labeled data sets may be hard to gather. Therefore, we wished to tackle here the problem of having insufficient training data. We examined lea…