Publications related to Cost estimation in software engineering

Stochastic adaptive resampling for the estimation of discrete choice models

Michel Bierlaire, Nicola Marco Ortelli, Matthieu Marie Cochon de Lapparent

In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

2023

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

Michel Bierlaire, Timothy Michael Hillel, Janody Pougala

Activity-based models offer the potential of a far deeper understanding of daily mobility behaviour than trip-based models. However, activity-based models used both in research and practice have often relied on applying sequential choice models between sub ...

2023

Parametric Estimation For Functional Autoregressive Processes On The Sphere

Alessia Caponera

The aim of this paper is to define a nonlinear least squares estimator for the spectral parameters of a spherical autoregressive process of order 1 in a parametric setting. Furthermore, we investigate on its asymptotic properties, such as weak consistency ...

2022

Challenges for biophysical modeling of microstructure

Ileana Ozana Jelescu

The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25 years. In this review, we dwell on the various challenges along the journey of bringing a biophysical model from initial design to clinical implementation, identifyi ...

2020

Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

Michel Bierlaire, Timothy Michael Hillel, Virginie Janine Camille Lurkin, Gael Lederrey

The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the esti ...

2021

Simultaneous autoregressive models for spatial extremes

Emeric Rolland Georges Thibaud

Motivated by the widespread use of large gridded data sets in the atmospheric sciences, we propose a new model for extremes of areal data that is inspired by the simultaneous autoregressive (SAR) model in classical spatial statistics. Our extreme SAR model ...

WILEY2020

Predicting learners' effortful behaviour in adaptive assessment using multimodal data

Kshitij Sharma, Jennifer Kaitlyn Olsen

Many factors influence learners' performance on an activity beyond the knowledge required. Learners' on-task effort has been acknowledged for strongly relating to their educational outcomes, reflecting how actively they are engaged in that activity. Howeve ...

ASSOC COMPUTING MACHINERY2020

Plug-and-Play Fault Detection and Isolation for Large-Scale Nonlinear Systems With Stochastic Uncertainties

Giancarlo Ferrari Trecate

This paper proposes a novel scalable model-based fault detection and isolation approach for the monitoring of nonlinear large-scale systems, consisting of a network of interconnected subsystems. The fault diagnosis architecture is designed to automatically ...

2019

Extreme flood estimations on a small alpine catchment in Switzerland, the case study of Limmerboden

Anton Schleiss, Javier García Hernández, Fränz Zeimetz

In this paper, a case study on the estimations of extreme floods is described. The watershed chosen for the analysis is the catchment of the Limmernboden dam situated in Switzerland. Statistical methods and the simulation based "Probable Maximum Precipitat ...

Copernicus Gesellschaft Mbh2015

On spurious and real fluctuations of dynamic functional connectivity during rest

Dimitri Nestor Alice Van De Ville, Nora Leonardi

Functional brain networks reconfigure spontaneously during rest. Such network dynamics can be studied by dynamic functional connectivity (dynFC); i.e., sliding-window correlations between regional brain activity. Key parameters-such as window length and cu ...

Elsevier2015

Expert Judgements in Risk Analysis: a Strategy to Overcome Uncertainities

Thierry Meyer, Amela Groso, David Nicolas Plüss

There is a need for a risk analysis technique specific for academic research laboratories. Since accurate accident data, normally required for quantitative risk analysis, are not available for this environment, expert judgements are often used to describe ...

2013

Wavelet-variance-based estimation for composite stochastic processes

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

This article presents a new estimation method for the parameters of a time series model. We consider here composite Gaussian processes that are the sum of independent Gaussian processes which, in turn, explain an important aspect of the time series, as is ...

Amer Statistical Assoc2013

Estimation of Sparse MIMO Channels with Common Support

Martin Vetterli, Ali Hormati, Yann Barbotin

We consider the problem of estimating sparse communication channels in the MIMO context. In small to medium bandwidth communications, as in the current standards for OFDM and CDMA communication systems (with bandwidth up to 20 MHz), such channels are indiv ...

2012

ESTIMATING SPARSE MIMO CHANNELS HAVING COMMON SUPPORT

Martin Vetterli, Ali Hormati, Yann Barbotin

According to a first aspect of the present invention there is provided a method of estimating, jointly, a set of multipath channels having a common path support, the method comprising the steps of, estimating jointly the common path support of the set of m ...

USPTO2012

Mmse Denoising Of Sparse Levy Processes Via Message Passing

Michaël Unser, Arash Amini, Ulugbek Kamilov

Many recent algorithms for sparse signal recovery can be interpreted as maximum-a-posteriori (MAP) estimators relying on some specific priors. From this Bayesian perspective, state-of-the-art methods based on discrete-gradient regularizers, such as total-v ...

Ieee2012

New Challenges in Disaggregate Behavioral Modeling : Emotions, Investments and Mobility

Thomas Robin

This thesis tackles new challenges associated with the disaggregate modeling of the human behavior. Decision-aid tools help in making decisions, by providing quantitative insights on the decisions and associated consequences. They are useful in complex sit ...

EPFL2011

Efficient Use of the Query Optimizer for Automated Database Design

Anastasia Ailamaki, Debabrata Dash

State-of-the-art database design tools rely on the query optimizer for comparing between physical design alternatives. Although it provides an appropriate cost model for physical design, query optimization is a computationally expensive process. The signif ...

2007

Travel Time Estimation on a Signalised Urban Networks using Cumulative Plots

André-Gilles Dumont, Ashish Bhaskar, Edward Chung

This paper presents the development and testing of a methodology for estimation of average travel time on signalised urban networks. The methodology considers the classical analytical procedure, where average travel time on a study link is estimated as the ...

2007

Methodology for Travel Time Estimation on a Signalised Arterial

André-Gilles Dumont, Ashish Bhaskar, Edward Chung

This paper presents the development and testing of a methodology for estimation of average travel time on signalised urban networks. The methodology considers the classical analytical procedure, where average travel time on a study link is estimated as the ...

2007

Tomographic approach for parametric estimation of local diffusive sources and application to heat diffusion

Martin Vetterli, Luciano Sbaiz, Ivana Jovanovic

We consider localized instantaneous sources that reside in a 2D dif- fusive environment. Our goal is to reconstruct the induced field from the measurements obtained by distributed sensors. Although the field is non-bandlimited, we capitalize on the fact th ...

2007