Publications associées à Coût d'opportunité

Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling

Robert West, Maxime Jean Julien Peyrard, Marija Sakota

Generative language models (LMs) have become omnipresent across data science. For a wide variety of tasks, inputs can be phrased as natural language prompts for an LM, from whose output the solution can then be extracted. LM performance has consistently be ...

Assoc Computing Machinery2024

Efficient Online Clustering with Moving Costs

Volkan Cevher, Efstratios Panteleimon Skoulakis

In this work we consider an online learning problem, called Online k-Clustering with Moving Costs, at which a learner maintains a set of k facilities over T rounds so as to minimize the connection cost of an adversarially selected sequence of clients. The ...

2023

Updates on Hydrogen Value Chain: A Strategic Roadmap

Michael Graetzel, Dan Ren

A strategic roadmap for noncarbonized fuels is a global priority, and the reduction of carbon dioxide emissions is a key focus of the Paris Agreement to mitigate the effects of rising temperatures. In this context, hydrogen is a promising noncarbonized fue ...

WILEY-V C H VERLAG GMBH2023

Sensitivity to user mischaracterizations in electric vehicle charging

Nils Gustav Nilsson

In this paper, we consider electric vehicle charging facilities that offer various levels of service, i.e., charging rates, for varying prices such that rational users choose a level of service that minimizes the total cost to themselves including an oppor ...

ELSEVIER2023

Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma

Jiancheng Yang, Li Zhang, Xinchao Wang, Hua Sun

Background: The nature of the solid component of subsolid nodules (SSNs) can indicate tumor pathological invasiveness. However, preoperative solid component assessment still lacks a reference standard.Methods: In this retrospective study, an AI algorithm w ...

Elsevier Ireland Ltd2023

Text Representation Learning for Low Cost Natural Language Understanding

Jan Frederik Jonas Florian Mai

Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...

EPFL2023

Appropriations and Uses of Travel Time

Ludy Juliana González Villamizar

Time has always been a central factor in understanding the challenges of daily mobility. For a long time, and still today, methods of economic evaluation of transport projects have monetized time savings so that they can be included in the cost–benefit ana ...

ISTE Wiley2023

A continuum approximation approach to the depot location problem in a crowd-shipping system

Nikolaos Geroliminis, Patrick Stefan Adriaan Stokkink

Last-mile delivery in the logistics chain contributes to congestion in urban networks due to frequent stops. Crowd-shipping is a sustainable and low-cost alternative to traditional delivery but relies heavily on the availability of occasional couriers. In ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm

Fernando Porté Agel, Nicolas Otto Kirchner Bossi

This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions ...

Pergamon-Elsevier Science Ltd2023

Nanocrystalline Flash Annealed Nickel Oxide for Large Area Perovskite Solar Cells

Michael Graetzel, Jovana Milic, Felix Thomas Eickemeyer

The industrialization of perovskite solar cells requires adequate materials and processes to make them economically viable and environmentally sustainable. Despite promising results in terms of power conversion efficiency and operational stability, several ...

WILEY2023

Hardware-Software co-design Methodologies for Edge AI Optimization

Flavio Ponzina

ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...

EPFL2023

Optimal Matching of Random Parts

Thomas Alois Weber

This paper examines the minimization of the cost for an expected random production output, given an assembly of finished goods from two random inputs, matched in two categories. We describe the optimal input portfolio, first using the standard normal appro ...

2022

Technology Strategy in Dynamic Environments: A Computational Analysis of the Automation of Routines, the Organization of AI, and the Evaluation of Technology Risk

Maximilian Wieland Hofer

In this dissertation, I develop theory and evidence to argue that new technologies are central to how firms organize to create and capture value. I use computational methods such as reinforcement learning and probabilistic topic modeling to investigate thr ...

EPFL2022

Modeling and mitigating supply chain disruptions as a bilevel network flow problem

Ralf Seifert, Anna Timonina-Farkas, René Yves Glogg

Years of globalization, outsourcing and cost cutting have increased supply chain vulnerability calling for more effective risk mitigation strategies. In our research, we analyze supply chain disruptions in a production setting. Using a bilevel optimization ...

2022

Hole transport material, synthesis thereof, and solar cell

Michael Graetzel, Shaik Mohammed Zakeeruddin, Yuhang Liu, Michael Bauer

The organic small molecule 4,4',4",4"'-(5,5-dimethoxycyclopenta-1,3-diene-1,2,3,4-tetrayl)tetrakis(N,N-bis(4-methoxyhenyl)aniline (CPDA 1), shows electrochemical properties very close to spiro-OMeTAD indicating a high compatibility with PSC systems for its ...

2022

Neural Energy Casimir Control for Port-Hamiltonian Systems

Giancarlo Ferrari Trecate, Muhammad Zakwan, Liang Xu

The energy Casimir method is an effective controller design approach to stabilize port-Hamiltonian systems at a desired equilibrium. However, its application relies on the availability of suitable Casimir and Lyapunov functions, whose computation are gener ...

2022

Online appendix to: Debt dynamics with fixed issuance costs

Julien Hugonnier

We investigate equilibrium debt dynamics for a firm that cannot commit to a future debt policy and is subject to a fixed restructuring cost. We formally characterize equilibria when the firm is not required to repurchase outstanding debt prior to issuing a ...

2022

Techno-Economic Evaluation of Biological and Fluidised-Bed Based Methanation Process Chains for Grid-Ready Biomethane Production

Oliver Kröcher, Tilman J. Schildhauer, Andreas Gantenbein

Three different power-to-methane process chains with grid injection in two scales (1 MWel and 6 MWel) were analysed regarding their investment and operation cost. The process chains were based on biological or catalytic bubbling fluidised bed methanation i ...

FRONTIERS MEDIA SA2022

Frequency dependence in GW made simple using a multipole approximation

Tommaso Chiarotti, Andrea Ferretti

In the GW approximation, the screened interaction W is a nonlocal and dynamical potential that usually has a complex frequency dependence. A full description of such a dependence is possible but often computationally demanding. For this reason, it is still ...

AMER PHYSICAL SOC2021

An analysis of the impacts of green mobility strategies and technologies on different European energy system

François Maréchal, Jonas Schnidrig, Tuong-Van Nguyen

A successful decarbonization of the European Union, coupled with a high integration of renewable energy and ambitious targets for energy efficiency, can only be reached with a significant contribution from transport. This sector currently represents a quar ...

2021