Publications related to Scalable Convex Methods for Phase Retrieval

An Augmented Lagrangian Coordination-Decomposition Algorithm for Solving Distributed Non-Convex Programs

A novel augmented Lagrangian method for solving non-convex programs with nonlinear cost and constraint couplings in a distributed framework is presented. The proposed decomposition algorithm is made of two layers: The outer level is a standard multiplier m ...

2014

An Augmented Lagrangian Coordination-Decomposition Algorithm for Solving Distributed Non-Convex Programs

Colin Neil Jones, Jean-Hubert Hours

A novel augmented Lagrangian method for solving non-convex programs with nonlinear cost and constraint couplings in a distributed framework is presented. The proposed decomposition algorithm is made of two layers: The outer level is a standard multiplier m ...

Ieee2014

Fast Proximal algorithms for Self-concordant function minimization with application to sparse graph selection

Volkan Cevher, Anastasios Kyrillidis

The convex

\ell_1

-regularized

\log\det

divergence criterion has been shown to produce theoretically consistent graph learning. However, this objective function is challenging since the

\ell_1

-regularization is nonsmooth, the

\log\det

objective is n ...

2013

Fast Proximal Algorithms For Self-Concordant Function Minimization With Application To Sparse Graph Selection

Volkan Cevher, Anastasios Kyrillidis

The convex l(1)-regularized log det divergence criterion has been shown to produce theoretically consistent graph learning. However, this objective function is challenging since the l(1)-regularization is nonsmooth, the log det objective is not globally Li ...

IEEE2013

Time-Optimal Path Following for Robots With Convex-Concave Constraints Using Sequential Convex Programming

Quoc Tran Dinh

Time-optimal path following considers the problem of moving along a predetermined geometric path in minimum time. In the case of a robotic manipulator with simplified constraints, a convex reformulation of this optimal control problem has been derived prev ...

Institute of Electrical and Electronics Engineers2013

Use of Convex Model Approximations for Real-Time Optimization via Modifier Adaptation

Dominique Bonvin, Grégory François

Real-Time Optimization (RTO) via modifier adaptation is a class of methods for which measurements are used to iteratively adapt the model via input-affine additive terms. The modifier terms correspond to the deviations between the measured and predicted co ...

American Chemical Society2013

Approximate dynamic programming via sum of squares programming

Maryam Kamgarpour, Tyler Summers

We describe an approximate dynamic programming method for stochastic control problems on infinite state and input spaces. The optimal value function is approximated by a linear combination of basis functions with coefficients as decision variables. By rela ...

2013

Certification Aspects of the Fast Gradient Method for Solving the Dual of Parametric Convex Programs

Colin Neil Jones

This paper examines the computational complexity certification of the fast gradient method for the solution of the dual of a parametric con- vex program. To this end, a lower iteration bound is derived such that for all parameters from a compact set a solu ...

Springer Heidelberg2012

Towards computational complexity certification for constrained mpc based on lagrange relaxation and the fast gradient method

Colin Neil Jones

Solving a convex optimization problem within an a priori certified period of time is a challenging problem. This paper discusses the certification of Nesterov’s fast gradient method for problems with a strictly quadratic objective and a feasible set given ...

2011

Temperature Control of High Performance Multicore Platforms Using Convex Optimization

Giovanni De Micheli, David Atienza Alonso, Luca Benini, Srinivasan Murali

With technology advances, the number of cores integrated on a chip and their speed of operation is increasing. This, in turn is leading to a significant increase in chip temperature. Temperature gradi- ents and hot-spots not only affect the performance of ...

2008

Scalable Convex Methods for Phase Retrieval

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An Augmented Lagrangian Coordination-Decomposition Algorithm for Solving Distributed Non-Convex Programs

An Augmented Lagrangian Coordination-Decomposition Algorithm for Solving Distributed Non-Convex Programs

Fast Proximal algorithms for Self-concordant function minimization with application to sparse graph selection

Fast Proximal Algorithms For Self-Concordant Function Minimization With Application To Sparse Graph Selection

Time-Optimal Path Following for Robots With Convex-Concave Constraints Using Sequential Convex Programming

Use of Convex Model Approximations for Real-Time Optimization via Modifier Adaptation

Approximate dynamic programming via sum of squares programming

Certification Aspects of the Fast Gradient Method for Solving the Dual of Parametric Convex Programs

Towards computational complexity certification for constrained mpc based on lagrange relaxation and the fast gradient method

Temperature Control of High Performance Multicore Platforms Using Convex Optimization

Use of Convex Model Approximations for Real-Time Optimization via Modifier Adaptation

Approximate dynamic programming via sum of squares programming

Towards computational complexity certification for constrained mpc based on lagrange relaxation and the fast gradient method

An Augmented Lagrangian Coordination-Decomposition Algorithm for Solving Distributed Non-Convex Programs

Fast Proximal algorithms for Self-concordant function minimization with application to sparse graph selection

An Augmented Lagrangian Coordination-Decomposition Algorithm for Solving Distributed Non-Convex Programs

Fast Proximal Algorithms For Self-Concordant Function Minimization With Application To Sparse Graph Selection

Time-Optimal Path Following for Robots With Convex-Concave Constraints Using Sequential Convex Programming

Certification Aspects of the Fast Gradient Method for Solving the Dual of Parametric Convex Programs

Temperature Control of High Performance Multicore Platforms Using Convex Optimization