Publications associées à Classification en classes multiples

MATHICSE Technical Report: Simulation-Based Anomaly Detection and Damage Localization: an Application to Structural Health Monitoring

Jan Sickmann Hesthaven, Caterina Bigoni

We propose a simulation-based decision strategy for the proactive maintenance of complex structures with a particular application to structural health monitoring (SHM). The strategy is based on a data-driven approach which exploits an offine-online decompo ...

MATHICSE2019

Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Wolfram Wiesemann

A fundamental problem arising in many areas of machine learning is the evaluation of the likelihood of a given observation under different nominal distributions. Frequently, these nominal distributions are themselves estimated from data, which makes them s ...

2019

Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments

Open-ended learning environments (OELEs) allow students to freely interact with the content and to discover important principles and concepts of the learning domain on their own. However, only some students possess the necessary skills for efficient and ef ...

International Educational Data Mining Society2019

Tailoring SVM Inference for Resource-Efficient ECG-Based Epilepsy Monitors

David Atienza Alonso, Giovanni Ansaloni, Amir Aminifar, Leila Cammoun

Event detection and classification algorithms are resilient towards aggressive resource-aware optimisations. In this paper, we leverage this characteristic in the context of smart health monitoring systems. In more detail, we study the attainable benefits ...

IEEE2019

Machine-learning Classifiers for Intermediate Redshift Emission-line Galaxies

Jean-Paul Richard Kneib, Johan Comparat, David Schlegel

Classification of intermediate redshift (z = 0.3-0.8) emission line galaxies as star-forming galaxies, composite galaxies, active galactic nuclei (AGNs), or low-ionization nuclear emission regions (LINERs) using optical spectra alone was impossible because ...

IOP PUBLISHING LTD2019

A machine learning approach for mapping the very shallow theoretical geothermal potential

Jean-Louis Scartezzini, Dan Assouline, Nahid Mohajeri Pour Rayeni

The very shallow geothermal potential (vSGP) is increasingly recognized as a viable resource for providing clean thermal energy in urban and rural areas. This is primarily due to its reliability, low-cost installation, easy maintenance, and little constrai ...

SPRINGEROPEN2019

Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatal I-123-FP-CIT indices

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti

ObjectivesTo provide an automated classification method for degenerative parkinsonian syndromes (PS) based on semiquantitative I-123-FP-CIT SPECT striatal indices and support-vector-machine (SVM) analysis.Methods(123)I-FP-CIT SPECT was performed at a singl ...

Springer2019

Evaluation Methodologies for Biometric Presentation Attack Detection

Sébastien Marcel, André Anjos, Ivana Chingovska, Amir Mohammadi

Presentation attack detection (PAD, also known as anti-spoofing) systems, regardless of the technique, biometric mode or degree of independence of external equipment, are most commonly treated as binary classification systems. The two classes that they dif ...

Springer International Publishing2019

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Classification en classes multiples

MATHICSE Technical Report: Simulation-Based Anomaly Detection and Damage Localization: an Application to Structural Health Monitoring

Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization

Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments

Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures

Topology classification with deep learning to improve real-time event selection at the LHC

Tailoring SVM Inference for Resource-Efficient ECG-Based Epilepsy Monitors

Machine-learning Classifiers for Intermediate Redshift Emission-line Galaxies

A machine learning approach for mapping the very shallow theoretical geothermal potential

Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatal I-123-FP-CIT indices

Evaluation Methodologies for Biometric Presentation Attack Detection

Graph Chatbot

Chattez avec Graph Search

MATHICSE Technical Report: Simulation-Based Anomaly Detection and Damage Localization: an Application to Structural Health Monitoring

Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization

Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures

Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments

A machine learning approach for mapping the very shallow theoretical geothermal potential

Evaluation Methodologies for Biometric Presentation Attack Detection

Topology classification with deep learning to improve real-time event selection at the LHC

Tailoring SVM Inference for Resource-Efficient ECG-Based Epilepsy Monitors

Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatal I-123-FP-CIT indices

Machine-learning Classifiers for Intermediate Redshift Emission-line Galaxies