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Concept

Admissible decision rule

Publications associées (14)

The Decision Rule Approach to Optimisation under Uncertainty: Methodology and Applications

Daniel Kuhn, Wolfram Wiesemann

Dynamic decision-making under uncertainty has a long and distinguished history in operations research. Due to the curse of dimensionality, solution schemes that naively partition or discretize the support of the random problem parameters are limited to sma ...

2019

Development of a methodology for extreme flood estimations in alpine catchments for the verification of dam safety

Fränz Zeimetz

In the context of dam safety, reliable safety flood estimation methods are necessary to guarantee a sufficiently designed spillway capacity. Todayâ s state of the art allows to approach this topic under different angles. Statistical extrapolations are com ...

EPFL2017

False arrhythmia alarms reduction in the intensive care unit: a multimodal approach

Jean-Marc Vesin, Sasan Yazdani, Sibylle Fallet

The purpose of this study was to develop algorithms to lower the incidence of false arrhythmia alarms in the ICU using information from independent sources, namely electrocardiogram (ECG), arterial blood pressure (ABP) and photoplethysmogram (PPG). Our app ...

Institute of Physics2016

Sparse Stochastic Processes and Discretization of Linear Inverse Problems

Michaël Unser, Ulugbek Kamilov, Emrah Bostan, Masih Nilchian

We present a novel statistically-based discretization paradigm and derive a class of maximum a posteriori (MAP) estimators for solving ill-conditioned linear inverse problems. We are guided by the theory of sparse stochastic processes, which specifies cont ...

Ieee-Inst Electrical Electronics Engineers Inc2013

A mixed random utility Random regret model linking the choice of decision rule to latent character traits

Amanda Blomberg Stathopoulos

An increasing number of studies are concerned with the use of alternatives to random utility maximisation as a decision rule in choice models, with a particular emphasis on regret minimisation over the last few years. The initial focus was on revealing whi ...

2013

Accelerated And Inexact Forward-Backward Algorithms

Luca Baldassarre

We propose a convergence analysis of accelerated forward-backward splitting methods for composite function minimization, when the proximity operator is not available in closed form, and can only be computed up to a certain precision. We prove that the 1/k( ...

Siam Publications2013

Learning Near-optimal Decision Rules for Energy Efficient Building Control

Colin Neil Jones

Recent studies suggest that advanced optimization based control methods such as model predictive control (MPC) can increase energy efficiency of buildings. However, adoption of these methods by industry is still slow, as building operators are used to work ...

2012

Learning Near-optimal Decision Rules for Energy Efficient Building Control

Colin Neil Jones

2012

Robust parameter estimation for the Ornstein-Uhlenbeck process

Sonja Rieder

In this paper, we derive elementary M- and optimally robust asymptotic linear (AL)-estimates for the parameters of an Ornstein-Uhlenbeck process. Simulation and estimation of the process are already well-studied, see Iacus (Simulation and inference for sto ...

Springer-Verlag2012

On the direct evaluation of surface integral equation impedance matrix elements involving point singularities

Juan Ramon Mosig, Athanasios Polymeridis

The direct evaluation method tailored to the 4-D singular integrals over vertex adjacent triangles, arising in the first-kind and second-kind Fredholm surface integral equation formulations, is presented. A combination of singularity cancellation, reorderi ...

Institute of Electrical and Electronics Engineers2011

Statistical Decision Making for Authentication and Intrusion Detection

Christos Dimitrakakis, Aikaterini Mitrokotsa

User authentication and intrusion detection differ from standard classification problems in that while we have data generated from legitimate users, impostor or intrusion data is scarce or non-existent. We review existing techniques for dealing with this p ...

2009

The Banff challenge: Statistical detection of a noisy signal

Anthony Christopher Davison

Particle physics experiments such as those run in the Large Hadron Collider result in huge quantities of data, which are boiled down to a few numbers from which it is hoped that a signal will be detected. We discuss a simple probability model for this and ...

2008

Probabilistic models for multi-classifier biometric authentication using quality measures

Jonas Richiardi

Biometric authentication can be cast as a signal processing and statistical pattern recognition problem. As such, it relies on models of signal representations that can be used to discriminate between classes. One of the assumptions typically made by the p ...

EPFL2008

A mixture model for multivariate extremes

Anthony Christopher Davison, Marc-Olivier Boldi

The spectral density function plays a key role in ﬁtting the tail of multivariate extremal data and so in estimating probabilities of rare events. This function satisﬁes moment constraints but unlike the univariate extreme value distributions has no simple ...

2007