Publications related to Blind Sensor Calibration in Sparse Recovery Using Convex Optimization

Designing Gabor windows using convex optimization

Redundant Gabor frames admit an infinite number of dual frames, yet only the canonical dual Gabor system, constructed from the minimal l(2)-norm dual window, is widely used. This window function however, might lack desirable properties, e. g. good time-fre ...

ELSEVIER SCIENCE INC2018

Convex Optimization using Sparsified Stochastic Gradient Descent with Memory

Jean-Baptiste Francis Marie Juliette Cordonnier

The interest for distributed stochastic optimization has raised to train complex Machine Learning models with more data on distributed systems. Increasing the computation power speeds up the training but it faces a communication bottleneck between workers ...

2018

A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization

Volkan Cevher, Anastasios Kyrillidis, Ya-Ping Hsieh, Rabeeh Karimi Mahabadi, Yu-Chun Kao

We study convex optimization problems that feature low-rank matrix solutions. In such scenarios, non-convex methods offer significant advantages over convex methods due to their lower space complexity as well as faster convergence speed. Moreover, many of ...

2018

A Data-Driven Approach to Power Converter Control via Convex Optimization

Alireza Karimi, Achille Nicoletti, Michele Martino

A new model reference data-driven approach is presented for synthesizing controllers for the CERN power converter control system. This method uses the frequency re- sponse function (FRF) of a system in order to avoid the problem of unmodeled dynamics assoc ...

2017

Robust Tracking Commitment

Colin Neil Jones, Tomasz Tadeusz Gorecki, Altug Bitlislioglu

Many engineering problems that involve hierarchical control applications, such as demand side ancillary service provision to the power grid, can be posed as a robust tracking commitment problem. In this setting, the lower-level controller commits a set of ...

2017

Combinatorial Penalties: Which structures are preserved by convex relaxations?

Volkan Cevher, Marwa El Halabi

We consider the homogeneous and the non-homogeneous convex relaxations for combinatorial penalty functions defined on support sets. Our study identifies key differences in the tightness of the resulting relaxations through the notion of the lower combinato ...

2017

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

Amir Aminifar

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

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

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

Robust Smith Predictor Design for Time-Delay Systems with H∞ Performance

Alireza Karimi, Achille Nicoletti, Vinicius De Oliveira

A new method for robust fixed-order H∞ controller design for uncertain time-delay systems is presented. It is shown that the H∞ robust performance condition can be represented by a set of convex constraints with respect to the parameters of a linearly para ...

Springer2015

Blind Sensor Calibration in Sparse Recovery Using Convex Optimization

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Designing Gabor windows using convex optimization

Convex Optimization using Sparsified Stochastic Gradient Descent with Memory

A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization

A Data-Driven Approach to Power Converter Control via Convex Optimization

Robust Tracking Commitment

Combinatorial Penalties: Which structures are preserved by convex relaxations?

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

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

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

Robust Smith Predictor Design for Time-Delay Systems with H∞ Performance

Convex Optimization using Sparsified Stochastic Gradient Descent with Memory

A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization

Combinatorial Penalties: Which structures are preserved by convex relaxations?

Designing Gabor windows using convex optimization

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

Robust Smith Predictor Design for Time-Delay Systems with H∞ Performance

A Data-Driven Approach to Power Converter Control via Convex Optimization

Robust Tracking Commitment

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

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