Publications related to K-Adaptability in Two-Stage Robust Binary Programming

Extreme Image Completion

Sabine Süsstrunk, Radhakrishna Achanta, Nikolaos Arvanitopoulos Darginis

It is challenging to complete an image whose 99 percent pixels are randomly missing. We present a solution to this extreme image completion problem. As opposed to existing techniques, our solution has a computational complexity that is linear in the number ...

Ieee2017

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

Daniel Kuhn, Grani Adiwena Hanasusanto, Wolfram Wiesemann

We propose to approximate two-stage distributionally robust programs with binary recourse decisions by their associated K-adaptability problems, which pre-select K candidate second-stage policies here-and-now and implement the best of these policies once t ...

Elsevier Science Bv2016

A Comment on “Computational Complexity of Stochastic Programming Problems”

Daniel Kuhn, Grani Adiwena Hanasusanto, Wolfram Wiesemann

Although stochastic programming problems were always believed to be computationally challenging, this perception has only recently received a theoretical justification by the seminal work of Dyer and Stougie (Mathematical Programming A, 106(3):423–432, 200 ...

Springer Heidelberg2016

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

Phase Transitions in Group Testing

Volkan Cevher, Jonathan Mark Scarlett

The group testing problem consists of determining a sparse subset of a set of items that are ``defective'' based on a set of possibly noisy tests, and arises in areas such as medical testing, fault detection, communication protocols, pattern matching, and ...

2016

Heat recovery networks synthesis of large-scale industrial sites: Heat load distribution problem with virtual process subsystems

François Maréchal, Nasibeh Pouransari

This paper presents a targeting strategy to design a heat recovery network for an industrial plant by dividing the system into subsystems while considering the heat transfer opportunities between them. The methodology is based on a sequential approach. The ...

Elsevier2015

Modified group delay feature based total variability space modelling for speaker recognition

In this paper, modified group delay (MODGD) features are used to model target speakers in the Total Variability Space (TVS) framework for speaker recognition. MODGD based features have been shown to improve speaker recognition performance owing to the abil ...

2015

Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

Anastasios Kyrillidis

Many natural and man-made signals can be described as having a few degrees of freedom relative to their size due to natural parameterizations or constraints; examples include bandlimited signals, collections of signals observed from multiple viewpoints in ...

EPFL2014

Stochastic MPC framework for controlling the average constraint violation

Colin Neil Jones, Milan Korda

This paper considers linear discrete-time systems with additive, bounded, disturbances subject to hard control input bounds and a stochastic constraint on the amount of state-constraint violation averaged over time. The amount of violations is quantified b ...

Institute of Electrical and Electronics Engineers2014

Enhanced Interpolated-DFT for Synchrophasor Estimation in FPGAs: Theory, Implementation, and Validation of a PMU Prototype

Mario Paolone, Paolo Romano

The literature on the subject of synchrophasor estimation (SE) algorithms has discussed the use of interpolated discrete Fourier transform (IpDFT) as an approach capable to find an optimal tradeoff between SE accuracy, response time, and computational comp ...

Institute of Electrical and Electronics Engineers2014

K-Adaptability in Two-Stage Robust Binary Programming

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Extreme Image Completion

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

A Comment on “Computational Complexity of Stochastic Programming Problems”

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Phase Transitions in Group Testing

Heat recovery networks synthesis of large-scale industrial sites: Heat load distribution problem with virtual process subsystems

Modified group delay feature based total variability space modelling for speaker recognition

Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

Stochastic MPC framework for controlling the average constraint violation

Enhanced Interpolated-DFT for Synchrophasor Estimation in FPGAs: Theory, Implementation, and Validation of a PMU Prototype

A Comment on “Computational Complexity of Stochastic Programming Problems”

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Extreme Image Completion

Phase Transitions in Group Testing

Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

Enhanced Interpolated-DFT for Synchrophasor Estimation in FPGAs: Theory, Implementation, and Validation of a PMU Prototype

Heat recovery networks synthesis of large-scale industrial sites: Heat load distribution problem with virtual process subsystems

Modified group delay feature based total variability space modelling for speaker recognition

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

Stochastic MPC framework for controlling the average constraint violation