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Identification of MIMO switched state-space models
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Learning nonlinear hybrid systems: from sparse optimization to support vector...
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Global convergence of a closed-loop regularized Newton method for solving mon...
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Augmented Lagrangian and Proximal Alternating Direction Methods of Multiplier...
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A dual approach to semidefinite least-squares problems
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Dequantizing compressed sensing: When oversampling and non-gaussian constrain...
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Dequantizing compressed sensing with non-gaussian constraints
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Combining the proximal algorithm and Tikhonov regularization
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A bundle-type algorithm for routing in telecommunication data networks
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Solving inverse problems with overcomplete transforms and convex optimization...
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Proximal method for geometry and texture image decomposition
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Optimisation convexe pour la cosegmentation
People and most animals have a natural ability to see the world and understand it effortlessly. The apparent simplicity of this task suggests that this ability is, to... -
A Multicomponent proximal algorithm for Empirical Mode Decomposition
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Optimization architecture for joint multi-path routing and scheduling in wire...
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Novel LMI conditions for observer-based stabilization of Lipschitzian nonline...
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A proximal approach for optimization problems involving Kullback divergences
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A proximal approach for signal recovery based on information measures
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Method for performing parallel magnetic resonance imaging
A method of parallel magnetic resonance imaging of a body, comprising: - acquiring a set of elementary magnetic resonance images of said body from respective receiving... -
Fast Convergence of Stochastic Gradient Descent under a Strong Growth Condition
We consider optimizing a function smooth convex function $f$ that is the average of a set of differentiable functions $f_i$, under the assumption considered by Solodov...
