Publications related to Stochastic

Sampling and (Sparse) Stochastic Processes: A Tale of Splines and Innovation

The commonality between splines and Gaussian or sparse stochastic processes is that they are ruled by the same type of differential equations. Our purpose here is to demonstrate that this has profound implications for the three primary forms of sampling: u ...

IEEE2015

Generalized Decision Rule Approximations for Stochastic Programming via Liftings

Daniel Kuhn, Wolfram Wiesemann

Stochastic programming provides a versatile framework for decision-making under uncertainty, but the resulting optimization problems can be computationally demanding. It has recently been shown that, primal and dual linear decision rule approximations can ...

Springer Verlag2015

Discriminative Learning of Deep Convolutional Feature Point Descriptors

Pascal Fua, Eduard Trulls Fortuny

Deep learning has revolutionalized image-level tasks such as classification, but patch-level tasks, such as correspondence, still rely on hand-crafted features, e.g. SIFT. In this paper we use Convolutional Neural Networks (CNNs) to learn discriminant patc ...

2015

Stochastic Modelling of Reservoir Sedimentation in a Semi-Arid Watershed

Nicolas Jean François Pascal Ghislain Adam, Michel Pirotton

Sedimentation in large reservoirs is a major concern in semi-arid regions characterized by severe seasonal water scarcity. As a contribution to improved sediment management, this study analyses the real case of the reservoir of Sidi Yacoub in the north of ...

2015

Thumbnail galleries for procedural models

Mark Pauly, Pablo Federico Mueller, Boris Neubert, Stefan Lienhard

Procedural modeling allows for the generation of innumerable variations of models from a parameterized, conditional or stochastic rule set. Due to the abstractness, complexity and stochastic nature of rule sets, it is often very difficult to have an unders ...

Wiley-Blackwell2014

Optimal Energy Management Strategy of an Improved Elevator With Energy Storage Capacity Based on Dynamic Programming

Alfred Rufer, Philippe Barrade

Efficiency and energy consumption reduction are becoming a key issue in elevation applications. Energy Storage Systems (ESS) can play a significant role in this field, together with their associated Energy Management Strategy (EMS) to optimize the overall ...

Institute of Electrical and Electronics Engineers2014

Near-Optimally Teaching the Crowd to Classify

Andreas Krause, Amin Karbasi, Ilija Bogunovic

How should we present training examples to learners to teach them classification rules? This is a natural problem when training workers for crowdsourcing labeling tasks, and is also moti- vated by challenges in data-driven online educa- tion. We propose a ...

2014

Comparison between reduced basis and stochastic collocation methods for elliptic problems

Alfio Quarteroni, Gianluigi Rozza, Peng Chen

The stochastic collocation method has recently been applied to stochastic problems that can be transformed into parametric systems. Meanwhile, the reduced basis method, primarily developed for solving parametric systems, has been recently used to deal with ...

Springer Verlag2014

Moment equations for the mixed formulation of the Hodge Laplacian with stochastic loading term

Fabio Nobile, Annalisa Buffa, Francesca Bonizzoni

We study the mixed formulation of the stochastic Hodge-Laplace problem dened on a

n

-dimensional domain

D (n ≥ 1)

, with random forcing term. In particular, we focus on the magnetostatic problem and on the Darcy problem in the three dimensional case. We ...

2014

Stochastic Resonance in Collective Exciton-Polariton Excitations inside a GaAs Microcavity

Benoît Marie Joseph Deveaud, François Morier-Genoud, Marcia Portella Oberli, Stéphane Trebaol, Hadis Abbaspour

We report the first observation of stochastic resonance in confined exciton polaritons. We evidence this phenomena by tracking the polaritons behavior through two stochastic resonance quantifiers namely the spectral magnification factor and the signal-to-n ...

American Physical Society2014

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Sampling and (Sparse) Stochastic Processes: A Tale of Splines and Innovation

Generalized Decision Rule Approximations for Stochastic Programming via Liftings

Discriminative Learning of Deep Convolutional Feature Point Descriptors

Stochastic Modelling of Reservoir Sedimentation in a Semi-Arid Watershed

Thumbnail galleries for procedural models

Optimal Energy Management Strategy of an Improved Elevator With Energy Storage Capacity Based on Dynamic Programming

Near-Optimally Teaching the Crowd to Classify

Comparison between reduced basis and stochastic collocation methods for elliptic problems

Moment equations for the mixed formulation of the Hodge Laplacian with stochastic loading term

Stochastic Resonance in Collective Exciton-Polariton Excitations inside a GaAs Microcavity

Generalized Decision Rule Approximations for Stochastic Programming via Liftings

Discriminative Learning of Deep Convolutional Feature Point Descriptors

Sampling and (Sparse) Stochastic Processes: A Tale of Splines and Innovation

Stochastic Modelling of Reservoir Sedimentation in a Semi-Arid Watershed

Thumbnail galleries for procedural models

Near-Optimally Teaching the Crowd to Classify

Stochastic Resonance in Collective Exciton-Polariton Excitations inside a GaAs Microcavity

Comparison between reduced basis and stochastic collocation methods for elliptic problems

Moment equations for the mixed formulation of the Hodge Laplacian with stochastic loading term

Optimal Energy Management Strategy of an Improved Elevator With Energy Storage Capacity Based on Dynamic Programming