Adaptive predictors based on probabilistic SVM for real time disruption mitigation on JET

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The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

Motivated by the transfer of proofs between proof systems, and in particular from first order automated theorem provers (ATPs) to interactive theorem provers (ITPs), we specify an extension of the TPTP derivation text format to describe proofs in first-ord ...

Energy efficiency is crucial for the sustainable operation of all industrial and urban sectors. However, practicing engineers have seldom access to open-source tools that can readily evaluate and compare scenarios in terms of energy consumption, cost, and ...

The Dynamic Aperture is an important concept for the study of non-linear beam dynamics in a circular accelerator. The DA is defined as the extent of the phase-space region in which the particle's motion remains bounded over a finite number of turns. Such a ...

Training science and engineering students to become responsible citizens and professionals requires novel and creative pedagogical approaches, such as design thinking. This concept relies on processes and tools to develop creativity and problem-solving ski ...

The opportunities provided by adopting digitally-generated visual tools in urban participatory planning are compelling. These visual tools can promote interactions between authorities and citizens and among citizens. However, the urban participatory practi ...

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that th ...

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

Many applications, e.g. in content recommendation, sports, or recruitment, leverage the comparisons of alternatives to score those alternatives. The classical Bradley-Terry model and its variants have been widely used to do so. The historical model conside ...

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

Revision behavior in adaptive writing support systems is an important and relatively new area of research that can improve the design and effectiveness of these tools, and promote students' self-regulated learning (SRL). Understanding how these tools are u ...

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 ...

Metal-based Laser Powder Bed Fusion (LPBF) has made fabricating intricate components easier. Yet, assessing part quality is inefficient, relying on costly Computed Tomography (CT) scans or time-consuming destructive tests. Also, intermittent inspection of ...

Logic rewriting is a powerful optimization technique that replaces small sections of a Boolean network with better implementations. Typically, exact synthesis is used to compute optimum replacement on-the-fly, with possible support for Boolean don't cares. ...

Pre-adoption phases of innovation are understudied in the innovation literature. This article addresses preadoption phases of innovation by running a prospective analysis. We assess the readiness of municipalities for the adoption of a digital tool that br ...

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

We develop an algorithm to solve the bottleneck assignment problem (BAP) that is amenable to having computation distributed over a network of agents. This consists of exploring how each component of the algorithm can be distributed, with a focus on one com ...

Visual data play a crucial role in modern society, and the rate at which images and videos are acquired, stored, and exchanged every day is rapidly increasing. Image compression is the key technology that enables storing and sharing of visual content in an ...

Adaptive predictors based on probabilistic SVM for real time disruption mitigation on JET

Chattez avec Graph Search

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

SC-TPTP: An Extension of the TPTP Derivation Format for Sequent-Based Calculus

ROSMOSE: A Web-based Optimization Tool to Aid Decision-making for the Design and Operation of Industrial and Urban Energy Systems

Accelerating Dynamic Aperture Evaluation Using Deep Neural Networks

Digital Intervention for Collaborative and Human-Centered Activities in Design-Based Learning Scenarios

Media Coverage of 3D Visual Tools Used in Urban Participatory Planning

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

On the Generalization of Stochastic Gradient Descent with Momentum

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons

Stability: a search for structure

Understanding Revision Behavior in Adaptive Writing Support Systems for Education

Understanding generalization and robustness in modern deep learning

Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

Scalable Logic Rewriting Using Don’t Cares

Assessing the readiness of municipalities for digital process innovation

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

A Distributed Augmenting Path Approach for the Bottleneck Assignment Problem

JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range