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06/16/2022
Introducing the Huber mechanism for differentially private low-rank matrix completion
Performing low-rank matrix completion with sensitive user data calls for...
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06/01/2022
The robust way to stack and bag: the local Lipschitz way
Recent research has established that the local Lipschitz constant of a n...
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10/28/2021
How to boost autoencoders?
Autoencoders are a category of neural networks with applications in nume...
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01/18/2021
On the Differentially Private Nature of Perturbed Gradient Descent
We consider the problem of empirical risk minimization given a database,...
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03/22/2020
Tune smarter not harder: A principled approach to tuning learning rates for shallow nets
Effective hyper-parameter tuning is essential to guarantee the performan...
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03/20/2020
What is the optimal depth for deep-unfolding architectures at deployment?
Recently, many iterative algorithms proposed for various applications su...
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05/28/2019
Concavifiability and convergence: necessary and sufficient conditions for gradient descent analysis
Convergence of the gradient descent algorithm has been attracting renewe...
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04/30/2018
