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A Method For Generation Of High-Nonlinear S-Boxes Based On Gradient Descent
nonlinearity symmetric ciphers
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2014/3/10
Criteria based on the analysis of the properties of vectorial Boolean functions for selection of substitutions (S-boxes) for symmetric cryptographic primitives are given. We propose an improved gradie...
Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression
Adaptivity averaged stochastic gradient descent local strong convexity logistic regression
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2013/4/28
In this paper, we consider supervised learning problems such as logistic regression and study the stochastic gradient method with averaging, in the usual stochastic approximation setting where observa...
Learning Model-Based Sparsity via Projected Gradient Descent
Model-Based Sparsity Projected Gradient Descent
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2012/11/22
Several convex formulation methods have been proposed previously for statistical estimation with structured sparsity as the prior. These methods often require a carefully tuned regularization paramete...
A gradient descent solution to the Monge-Kantorovich problem
Monge-Kantorovich problem optimal transport
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2010/9/13
We present a new, simple, and elegant algorithm for computing the optimal mapping for the Monge-Kantorovich problem with quadratic cost. The method arises from a reformulation of the dual problem into...