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Publications associées (126)

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

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 ...

Clare2023

Reconstructing lensless image with ML models and deploying them onto embedded systems

Jonathan Philippe Reymond

Lensless imaging provides a large panel of benefits : cost, size, weight, etc., that are crucial for wearable application, IoT or medical devices. Such setups require the design of reconstruction algorithms to recover the image from the captured measuremen ...

2023

Nanocrystalline Flash Annealed Nickel Oxide for Large Area Perovskite Solar Cells

Felix Thomas Eickemeyer, Jovana Milic

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

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

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

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 ...

SPRINGER HEIDELBERG2022

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