Publications related to FAST TV-L1 OPTICAL FLOW FOR INTERACTIVITY

Combinatorial Penalties: Which structures are preserved by convex relaxations?

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

Architecture and coevolution of allosteric materials

Matthieu Wyart, Carolina Brito Carvalho dos Santos, Riccardo Ravasio

We introduce a numerical scheme to evolve functional elastic materials that can accomplish a specified mechanical task. In this scheme, the number of solutions, their spatial architectures, and the correlations among them can be computed. As an example, we ...

National Academy of Sciences2017

Scampi: a robust approximate message-passing framework for compressive imaging

Florent Gérard Krzakala, Jean François Emmanuel Barbier

Reconstruction of images from noisy linear measurements is a core problem in image processing, for which convex optimization methods based on total variation (TV) minimization have been the long-standing state-of-the-art. We present an alternative probabil ...

Iop Publishing Ltd2016

On the influence of momentum acceleration on online learning

Ali H. Sayed, Bicheng Ying, Kun Yuan

The article examines in some detail the convergence rate and mean-square-error performance of momentum stochastic gradient methods in the constant step-size and slow adaptation regime. The results establish that momentum methods are equivalent to the stand ...

2016

Structure Tensor Total Variation

Michaël Unser, Stamatios Lefkimmiatis

We introduce a novel generic energy functional that we employ to solve inverse imaging problems within a variational framework. The proposed regularization family, termed as structure tensor total variation (STV), penalizes the eigenvalues of the structure ...

SIAM2015

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

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

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

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

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

FAST TV-L1 OPTICAL FLOW FOR INTERACTIVITY

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Combinatorial Penalties: Which structures are preserved by convex relaxations?

Architecture and coevolution of allosteric materials

Scampi: a robust approximate message-passing framework for compressive imaging

On the influence of momentum acceleration on online learning

Structure Tensor Total Variation

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

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

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

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

Architecture and coevolution of allosteric materials

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

Combinatorial Penalties: Which structures are preserved by convex relaxations?

Composite convex minimization involving self-concordant-like cost functions

On the influence of momentum acceleration on online learning

Composite convex minimization involving self-concordant-like cost functions

Scampi: a robust approximate message-passing framework for compressive imaging

Structure Tensor Total Variation

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