We consider a multi-agent framework for distributed optimization where each agent has access to local smooth strongly convex function, and the collective goal is achieve consensus on parameters that minimize sum of agents' functions. propose an algorithm wherein operates asynchronously independently other agents. When functions are strongly-convex with Lipschitz-continuous gradients, we show it...

In this paper‎, ‎two extended three-term conjugate gradient methods based on the Liu-Storey ({tt LS})‎ ‎conjugate gradient method are presented to solve unconstrained optimization problems‎. ‎A remarkable property of the proposed methods is that the search direction always satisfies‎ ‎the sufficient descent condition independent of line search method‎, ‎based on eigenvalue analysis‎. ‎The globa...

Sequential optimality conditions provide adequate theoretical tools to justify stopping criteria for nonlinear programming solvers. Here, nonsmooth approximate gradient projection and complementary approximate Karush-Kuhn-Tucker conditions are presented. These sequential optimality conditions are satisfied by local minimizers of optimization problems independently of the fulfillment of constrai...

We propose a novel coding theoretic framework for mitigating stragglers in distributed learning. We show how carefully replicating data blocks and coding across gradients can provide tolerance to failures and stragglers for synchronous Gradient Descent. We implement our scheme in MPI and show how we compare against baseline architectures in running time and generalization error.

The standard geometrical shape optimization method proceed by the application of successive diffeomorphisms close to the identity starting from an initial guessed shape. Consequently, it does not allow for the optimization of the topology which is kept unchanged from one iteration to the other. The topological gradient enables to determine if the inclusion of a small hole of given shape is cost...

In this research, the bending analysis of rectangular nanoplates subjected to mechanical loading is investigated. For this purpose, the strain gradient elasticity theory with one gradient parameter is presented to study the nanoplates. From the best knowledge of authors, it is the first time that the exponential shear deformation formulation based on strain gradient elasticity theory is carried...

The forced vibration behaviors are examined for nonlocal strain gradient nanobeams with surface effects subjected to a moving harmonic load travelling with a constant velocity in terms of three beam models namely, the Euler-Bernoulli, Timoshenko and modified Timoshenko beam models. The modification for nonlocal strain gradient Timoshenko nanobeams is exerted to the constitutive equations by exc...

The Bicoid (Bcd) protein gradient is generally believed to be established in pre-blastoderm Drosophila embryos by the diffusion of Bcd protein after translation of maternal mRNA, which serves as a strictly localized source of Bcd at the anterior pole. However, we previously published evidence that the Bcd gradient is preceded by a bcd mRNA gradient. Here, we have revisited and extended this obs...