Publications associées à Overcoming Incomplete User Models in Recommendation Systems Via an Ontology

Design ontology for cognitive thread supporting traceability management in model-based systems engineering

Industrial information integration engineering (IIIE) is an interdisciplinary field to facilitate the industrial information integration process. In the age of complex and large-scale systems, model-based systems engineering (MBSE) is widely adopted in ind ...

Elsevier2024

Ontology-based Knowledge Representation for Traditional Martial Arts

Yumeng Hou, Sarah Irene Brutton Kenderdine

Traditional martial arts are treasures of humanity's knowledge and critical carriers of sociocultural memories throughout history. However, such treasured practices have encountered various challenges in knowledge transmission and now feature many entries ...

2024

A semantic model-based systems engineering approach for assessing the operational performance of metal forming process

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

Metal Forming is a basic and essential industrial process to provide materials for constructing complex products. To design an efficient metal forming process, the functional requirements and operational performance are two important aspects to be consider ...

Pergamon-Elsevier Science Ltd2024

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Tradition ...

Elsevier Sci Ltd2024

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Anastasiia Koloskova

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

Machine learning-aided generative molecular design

Philippe Schwaller, Jeff Guo

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

Understanding generalization and robustness in modern deep learning

Maksym Andriushchenko

In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...

EPFL2024

An Ontology-based Engineering system to support aircraft manufacturing system design

Jinzhi Lu, Xiaochen Zheng

During the conceptual design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated against performance indicators in a collaborative engineering process. Domain experts' knowledge and the motivations for decision-ma ...

ELSEVIER SCI LTD2023

Co-encoding embodied knowledge in Southern Chinese martial arts: a collaboration between computists, experts, and digital models

Yumeng Hou

This research, within the framework of computational archives, inspects a novel approach to representing intangible knowledge in traditional martial arts. The methodology presents a unity of ontological modeling, semantic annotation, and feature-based mach ...

Zenodo2023

Building a Knowledge Graph of Chinese Kung Fu Masters From Heterogeneous Bilingual Data

Lin Yuan, Yumeng Hou

Various endeavours into semantic web technologies and ontology engineering have been made within the organisation of cultural data, facilitating public access to digital assets. Although models for conceptualising objects have reached a certain level of ma ...

2023

The inductive bias of deep learning: Connecting weights and functions

Guillermo Ortiz Jimenez

Years of a fierce competition have naturally selected the fittest deep learning algorithms. Yet, although these models work well in practice, we still lack a proper characterization of why they do so. This poses serious questions about the robustness, trus ...

EPFL2023

A semi-supervised algorithm for improving the consistency of crowdsourced datasets: The COVID-19 case study on respiratory disorder classification

David Atienza Alonso, Lara Orlandic, Tomas Teijeiro Campo

Background and Objective: Cough audio signal classification is a potentially useful tool in screening for respiratory disorders, such as COVID-19. Since it is dangerous to collect data from patients with contagious diseases, many research teams have turned ...

2023

Assessing the implementation of user-centred design standards on assistive technology for persons with visual impairments: a systematic review

Klaus Benedikt Schönenberger, Mario Andres Chavarria Varon

Despite scientific and technological advances in the field of assistive technology (AT) for people with visual impairment (VI), technological designs are frequently based on a poor understanding of the physical and social context of use, resulting in devic ...

Frontiers Media Sa2023

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Yuejiang Liu

Interactions are ubiquitous in our world, spanning from social interactions between human individuals to physical interactions between robots and objects to mechanistic interactions among different components of an intelligent system. Despite their prevale ...

EPFL2023

SELF-SUPERVISED ISOTROPIC SUPERRESOLUTION FETAL BRAIN MRI

Michaël Unser, Meritxell Bach Cuadra

Superresolution T2-weighted fetal-brain magnetic-resonance imaging (FBMRI) traditionally relies on the availability of several orthogonal low-resolution series of 2-dimensional thick slices (volumes). In practice, only a few low-resolution volumes are acqu ...

IEEE2023

Adapting Haptic Feedback for Guided Meditation

Nicolas Henchoz, Cédric Duchene, Andreas Sonderegger, Romain Simon Collaud, Emily Clare Groves, Yoann Pierre Douillet

Technology supporting meditation is a multimillion-dollar market that continues to grow. There is also strong academic interest to understand and improve the impact technology can have for the user experience of practitioners. However, little work investig ...

2023

Euclid preparation XXII. Selection of quiescent galaxies from mock photometry using machine learning

Georges Meylan, Frédéric Courbin, Fabio Finelli, Richard Massey, Maurizio Martinelli, Gianluca Castignani, Marcello Farina, Austin Chandler Peel, Yi Wang

The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across similar to 15 000deg(2) of the sky. Euclid is expected to detect similar to 12 billion astronomical source ...

EDP SCIENCES S A2023

Keep Sensors in Check: Disentangling Country-Level Generalization Issues in Mobile Sensor-Based Models with Diversity Scores

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Machine learning models trained with passive sensor data from mobile devices can be used to perform various inferences pertaining to activity recognition, context awareness, and health and well-being. Prior work has improved inference performance through t ...

Assoc Computing Machinery2023