Publications associées à An empirical comparison of travel choice models that capture preferences for compromise alternatives

Publications associées (28)

Optimal regimes for algorithm-assisted human decision-making

Mats Julius Stensrud, Aaron Leor Sarvet, Julien David Laurendeau

We consider optimal regimes for algorithm-assisted human decision-making. Such regimes are decision functions of measured pre-treatment variables and, by leveraging natural treatment values, enjoy a superoptimality property whereby they are guaranteed to o ...

2024

Reliable data-driven decision-making through optimal transport

Bahar Taskesen

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

EPFL2024

OASIS: An integrated optimisation framework for activity scheduling

Janody Pougala

Activity-based models offer the potential for a far deeper understanding of daily mobility behaviour than trip-based models. Based on the fundamental assumption that travel demand is derived from the need to do activities, they are flexible tools that aim ...

EPFL2024

Unveiling the complexity of learning and decision-making

Wei-Hsiang Lin

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

EPFL2024

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

EPFL2024

Neurobiological and metabolic basis of motivation and effort-based decision-making - A human 1H-MRS, fMRI and machine learning study

Arthur Barakat

Motivation is a multifaceted phenomenon that we explore within the framework of decision-making. Through this cognitive process, actions are directed towards specific goals by performing a trade-off between the cost and benefit of an action. The dorsomedia ...

EPFL2024

Stochastic adaptive resampling for the estimation of discrete choice models

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

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

Demand-based operations of vehicle sharing systems

Selin Ataç

Vehicle sharing systems (VSSs) allow users to rent vehicles for a short period of time, in a more flexible and convenient manner compared to the traditional vehicle rental services. The long-term VSS subscription replaces the need for contract signing for ...

EPFL2023

Contextual Stochastic Bilevel Optimization

Daniel Kuhn, Andreas Krause, Yifan Hu

We introduce contextual stochastic bilevel optimization (CSBO) -- a stochastic bilevel optimization framework with the lower-level problem minimizing an expectation conditioned on some contextual information and the upper-level decision variable. This fram ...

2023

Safety risk management in University laboratories

Anastasia Jung

Risk management has become an essential element in the functioning of modern society. Correct risk identification and assessment are undoubtedly crucial to improving overall safety; nevertheless, often, it is accompanied by the wrong selection of correctiv ...

EPFL2023

Decision support for the design of integrated biorefineries

Julia Granacher

A shift from fossil-based energy and products to more sustainable alternatives is essential to reduce greenhouse gas emissions and associated climate change impacts. Biomass represents a promising alternative for providing fuels and carbon-based products w ...

EPFL2023

Multi-agent Learning with Privacy Guarantees

Elsa Rizk

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

EPFL2023

End-to-End Learning for Stochastic Optimization: A Bayesian Perspective

Daniel Kuhn, Tobias Sutter, Yves Rychener

We develop a principled approach to end-to-end learning in stochastic optimization. First, we show that the standard end-to-end learning algorithm admits a Bayesian interpretation and trains a posterior Bayes action map. Building on the insights of this an ...

2023

How Words Move Hearts: Interpretable Machine Learning Models of Bias, Engagement, and Influence in Socio-Political Systems

Aswin Suresh

We study socio-political systems in representative democracies. Motivated by problems that affect the proper functioning of the system, we build computational methods to answer research questions regarding the phenomena occurring in them. For each phenomen ...

EPFL2023

Discovering perceived images of reused industrial heritage from user-generated photographs: Three mega-event reinforced industrial heritage transformation cases

Huishu Deng

Cities are increasingly reusing industrial heritage as part of cultural and creative regeneration strategies. However, designers and decision-makers face the challenge of determining which features and elements of industrial heritage are more perceived and ...

Springer2024

Maneuvering the odds: The dynamics of venture capital decision-making

Marc Gruber

Research Summary: This article investigates venture capital (VC) decision-making, a process that occurs under changing conditions and limited, ambiguous information. We shed new light on the inherent dynamics of this strategic process. One of the key disti ...

WILEY2023

Simulating intra-household interactions for in- and out-of-home activity scheduling

Michel Bierlaire, Timothy Michael Hillel, Negar Rezvany

Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of a household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly base ...

Pergamon-Elsevier Science Ltd2023

Data-driven modeling of beam loss in the LHC

Tatiana Pieloni, Michael Schenk, Ekaterina Krymova, Loïc Thomas Davies Coyle

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

FRONTIERS MEDIA SA2023

A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections

Michel Bierlaire

Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the last decade. Understanding the demand for these services is essential for planning and managing modern transportation systems. Existing studies develop statistical mod ...

2023

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023