Publications associées à Efficient Online Clustering with Moving Costs

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

Maxime Jean Julien Peyrard, Robert West, 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

Planetary-Scale Byzantine Fault Tolerance

Matteo Monti

The scale and pervasiveness of the Internet make it a pillar of planetary communication, industry and economy, as well as a fundamental medium for public discourse and democratic engagement. In stark contrast with the Internet's decentralized infrastructur ...

EPFL2024

Biodiesel from Bark and Black Liquor-A Techno-Economic, Social, and Environmental Assessment

Julia Granacher

A techno-economic assessment and environmental and social sustainability assessments of novel Fischer-Tropsch (FT) biodiesel production from the wet and dry gasification of biomass-based residue streams (bark and black liquor from pulp production) for tran ...

MDPI2024

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

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

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

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

Improving K-means Clustering Using Speculation

Anastasia Ailamaki, Viktor Sanca, Eleni Zapridou, Stefan Igescu

K-means is one of the fundamental unsupervised data clustering and machine learning methods. It has been well studied over the years: parallelized, approximated, and optimized for different cases and applications. With increasingly higher parallelism leadi ...

2023

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

Lead immobilization for environmentally sustainable perovskite solar cells

Michael Graetzel, Hui Zhang, Antonio Abate

Lead halide perovskites are promising semiconducting materials for solar energy harvesting. However, the presence of heavy-metal lead ions is problematic when considering potential harmful leakage into the environment from broken cells and also from a publ ...

NATURE PORTFOLIO2023

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

Xinchao Wang, Hua Sun, Li Zhang, Jiancheng Yang

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

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

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

Impact of Redundancy on Resilience in Distributed Optimization and Learning

Shuo Liu, Nirupam Gupta

This paper considers the problem of resilient distributed optimization and stochastic learning in a server-based architecture. The system comprises a server and multiple agents, where each agent has its own local cost function. The agents collaborate with ...

Assoc Computing Machinery2023

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

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

Hole transport material, synthesis thereof, and solar cell

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

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

Enabling renewable Europe through optimal design and operation

Alessio Santecchia

Europe is currently transitioning from fossil energy sources to renewable generation of electric power. Although fundamental to reach net-zero targets, intermittent renewables are disrupting conventional methods used in operational planning and design of p ...

EPFL2022

A note on universal inference

Anthony Christopher Davison, Timmy Rong Tian Tse

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

WILEY2022