Concept

Interior-point method

Related publications (197)

Scalable Convex Methods for Phase Retrieval

Volkan Cevher, Alp Yurtsever, Ya-Ping Hsieh

This paper describes scalable convex optimization methods for phase retrieval. The main characteristics of these methods are the cheap per-iteration complexity and the low-memory footprint. With a variant of the original PhaseLift formulation, we first ill ...

2015

A Convex Solution to Disparity Estimation from Light Fields via the Primal-Dual Method

Pierre Vandergheynst, Mahdad Hosseini Kamal

We present a novel approach to the reconstruction of depth from light field data. Our method uses dictionary representations and group sparsity constraints to derive a convex formulation. Although our solution results in an increase of the problem dimensio ...

Springer-Verlag Berlin2015

Composite convex minimization involving self-concordant-like cost functions

Volkan Cevher, Quoc Tran Dinh, Yen-Huan Li

The self-concordant-like property of a smooth convex func- tion is a new analytical structure that generalizes the self-concordant notion. While a wide variety of important applications feature the self- concordant-like property, this concept has heretofor ...

2015

Composite convex minimization involving self-concordant-like cost functions

Volkan Cevher, Quoc Tran Dinh, Yen-Huan Li

Abstract. The self-concordant-like property of a smooth convex func- tion is a new analytical structure that generalizes the self-concordant notion. While a wide variety of important applications feature the self- concordant-like property, this concept has ...

2015

Evaluating direct transcription and nonlinear optimization methods for robot motion planning

Jonas Buchli, Alexander Winkler

This paper studies existing direct transcription methods for trajectory optimization for robot motion planning. These methods have demonstrated to be favorable for planning dynamically feasible motions for high dimensional robots with complex dynamics. How ...

2015

Active Learning of Self-concordant like Multi-index Functions

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

We study the problem of actively learning a multi-index function of the form f (x) = g_0 (A_0 x) from its point evaluations, where A_0 ∈ R_{k×d} with k ≪ d. We build on the assumptions and techniques of an existing approach based on low-rank matrix recover ...

2015

Composite Self-Concordant Minimization

Volkan Cevher, Quoc Tran Dinh, Anastasios Kyrillidis

We propose a variable metric framework for minimizing the sum of a self-concordant function and a possibly non-smooth convex function endowed with a computable proximal operator. We theoretically establish the convergence of our framework without relying o ...

Massachusetts Institute of Technology Press2015

Graph-based denoising for time-varying point clouds

Pierre Vandergheynst, Johann Paratte, Yann Mikaël Schoenenberger

Noisy 3D point clouds arise in many applications. They may be due to errors when creating a 3D model from images or simply to imprecise depth sensors. Point clouds can be given geometrical structure using graphs created from the similarity information betw ...

2015

Fixed-order SISO controller design for H∞ loop shaping method using frequency responses

Alireza Karimi

Robust control is used for a system with uncertainties and disturbances. Above all, the H∞ loop shaping method is known as the method achieving good control performance. However, this method takes much time to build the mathematical model of an actual plan ...

IEEE2015

Stability and Performance Limits of Adaptive Primal-Dual Networks

Ali H. Sayed

This paper studies distributed primal-dual strategies for adaptation and learning over networks from streaming data. Two first-order methods are considered based on the Arrow-Hurwicz (AH) and augmented Lagrangian (AL) techniques. Several revealing results ...

IEEE2015

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