Publications related to Regularized Bundle Methods for Convex and Non-Convex Risks

Intrusion-Damage Assessment and Mitigation in Cyber-Physical Systems for Control Applications

With cyber-physical systems opening to the outside world, security can no longer be considered a secondary issue. One of the key aspects in security of cyber-phyiscal systems is to deal with intrusions. In this paper, we highlight the several unique proper ...

Assoc Computing Machinery2016

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

Volkan Cevher

This paper proposes a tradeoff between computational time, sample complexity, and statistical accuracy that applies to statistical estimators based on convex optimization. When we have a large amount of data, we can exploit excess samples to decrease stati ...

Ieee-Inst Electrical Electronics Engineers Inc2015

Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

In recent works, sparse models and convex optimization techniques have been applied to radio-interferometric (RI) imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. In this talk, I will review our latest contribut ...

2015

Proximal diffusion for stochastic costs with non-differentiable regularizers

Ali H. Sayed, Stefan Vlaski

We consider networks of agents cooperating to minimize a global objective, modeled as the aggregate sum of regularized costs that are not required to be differentiable. Since the subgradients of the individual costs cannot generally be assumed to be unifor ...

IEEE2015

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

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

Alireza Karimi, Achille Nicoletti, Zlatko Emedi

In this paper, a new method for designing robust fixed-order

\mathcal{H}_{\infty}

discrete-time controllers is presented. The controller structure is a two-degree of freedom polynomial controller of the

RST

type. A data-driven approach is implemented f ...

IEEE2015

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Jean-Philippe Thiran, Yves Wiaux, Erick Jorge Canales Rodriguez, Alessandro Daducci, Anna Auria Rasclosa, Tim Bjørn Dyrby

Mapping the local microstructure properties of the tissue in the brain is crucial to understand any pathological condition from a biological perspective. In recent years, microstructure-imaging techniques aimed at extracting such precious information by us ...

2015

Design of a Switching Controller for Adaptive Disturbance Attenuation with Guaranteed Stability

Alireza Karimi

In this paper, a new algorithm is proposed for the design of a family of controllers to be used within an adaptive switching control scheme. The resulting switching controller is able to attenuate the effects of disturbances having uncertain and possibly t ...

2015

A scalable algorithm for radio-interferometric imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Vijay Kartik

In recent works, sparse models and convex optimization techniques have been applied to radio-interferometric (RI) imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. In this paper, we propose a scalable algorithm f ...

2015

Regularized Bundle Methods for Convex and Non-Convex Risks

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Intrusion-Damage Assessment and Mitigation in Cyber-Physical Systems for Control Applications

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging

Proximal diffusion for stochastic costs with non-differentiable regularizers

Composite convex minimization involving self-concordant-like cost functions

Composite convex minimization involving self-concordant-like cost functions

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Design of a Switching Controller for Adaptive Disturbance Attenuation with Guaranteed Stability

A scalable algorithm for radio-interferometric imaging

Proximal diffusion for stochastic costs with non-differentiable regularizers

A scalable algorithm for radio-interferometric imaging

Intrusion-Damage Assessment and Mitigation in Cyber-Physical Systems for Control Applications

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

Composite convex minimization involving self-concordant-like cost functions

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Design of a Switching Controller for Adaptive Disturbance Attenuation with Guaranteed Stability

Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging

Composite convex minimization involving self-concordant-like cost functions