Publications related to Optimization Of Compound Regularization Parameters Based On Stein'S Unbiased Risk Estimate

Simulation based Synthesis of Population

Michel Bierlaire, Gunnar Flötteröd, Bilal Farooq, Ricardo Daniel Hurtubia González

Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and ...

2013

Simulations of driven overdamped frictionless hard spheres

Matthieu Wyart

Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and ...

Elsevier2013

Population Synthesis: A Different Perspective

Michel Bierlaire, Bilal Farooq

Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and ...

2013

Simulation based population synthesis

Michel Bierlaire, Gunnar Flötteröd, Bilal Farooq, Ricardo Daniel Hurtubia González

Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and ...

2013

Simulation based population synthesis

Michel Bierlaire, Gunnar Flötteröd, Bilal Farooq, Ricardo Daniel Hurtubia González

Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and ...

Pergamon-Elsevier Science Ltd2013

Bayesian Denoising: From MAP to MMSE Using Consistent Cycle Spinning

Michaël Unser, Emrah Bostan, Ulugbek Kamilov, Abbas Kazerouni

We introduce a new approach for the implementation of minimum mean-square error (MMSE) denoising for signals with decoupled derivatives. Our method casts the problem as a penalized least-squares regression in the redundant wavelet domain. It exploits the l ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Sparse Distributed Learning Based on Diffusion Adaptation

Ali H. Sayed

This article proposes diffusion LMS strategies for distributed estimation over adaptive networks that are able to exploit sparsity in the underlying system model. The approach relies on convex regularization, common in compressive sensing, to enhance the d ...

IEEE2013

On L2-Regularization for Virtual Reference Feedback Tuning

Alireza Karimi

The Virtual Reference Feedback Tuning (VRFT) approach is a design method that allow optimal feedback control laws to be derived from input-output (I/O) data only, without need of a model of the process. A drawback of this methods is that, in its standard f ...

2013

Manifold Sparse Beamforming

Volkan Cevher, Afsaneh Asaei, Baran Gözcü

We consider the minimum variance distortionless response (MVDR) beamforming problems where the array covariance matrix is rank deficient. The conventional approach handles such rank-deficiencies via diagonal loading on the covariance matrix. In this settin ...

2013

Manifold Sparse Beamforming

Volkan Cevher, Afsaneh Asaei, Baran Gözcü

We consider the minimum variance distortionless response (MVDR) beamforming problems where the array covariance matrix is rank deficient. The conventional approach handles such rank-deficiencies via diagonal loading on the covariance matrix. In this settin ...

IEEE2013

Optimization Of Compound Regularization Parameters Based On Stein'S Unbiased Risk Estimate

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Simulation based Synthesis of Population

Simulations of driven overdamped frictionless hard spheres

Population Synthesis: A Different Perspective

Simulation based population synthesis

Simulation based population synthesis

Bayesian Denoising: From MAP to MMSE Using Consistent Cycle Spinning

Sparse Distributed Learning Based on Diffusion Adaptation

On L2-Regularization for Virtual Reference Feedback Tuning

Manifold Sparse Beamforming

Manifold Sparse Beamforming

Manifold Sparse Beamforming

Manifold Sparse Beamforming

On L2-Regularization for Virtual Reference Feedback Tuning

Sparse Distributed Learning Based on Diffusion Adaptation

Population Synthesis: A Different Perspective

Simulations of driven overdamped frictionless hard spheres

Simulation based Synthesis of Population

Bayesian Denoising: From MAP to MMSE Using Consistent Cycle Spinning

Simulation based population synthesis

Simulation based population synthesis