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Rozprawy doktorskie na temat „Machine learning interactif”

Autor: Grafiati

Data publikacji: 14 grudnia 2024

Data aktualizacji: 31 lipca 2025

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Scurto, Hugo. "Designing With Machine Learning for Interactive Music Dispositifs." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS356.

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La musique est une pratique culturelle permettant aux êtres humains d'exprimer sensiblement leurs intentions à travers le son. L'apprentissage machine définit un ensemble de modèles permettant de nouvelles formes d'expression au sein desdits systèmes interactifs musicaux. Cependant, en tant que discipline informatique, l'apprentissage machine demeure essentiellement appliquée à la musique du point de vue des sciences de l'ingénieur, qui, très souvent, conçoit les modèles d'apprentissage sans tenir compte des interactions musicales prenant place entre humains et systèmes. Dans cette thèse, j'en

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Gosselin, Philippe-Henri. "Apprentissage interactif pour la recherche par le contenu dans les bases multimédias." Habilitation à diriger des recherches, Université de Cergy Pontoise, 2011. http://tel.archives-ouvertes.fr/tel-00660316.

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Les bases actuelles de données multimédia nécessitent des outils de plus en plus avancés pour pouvoir être parcourues avec efficacité. Dans ce contexte, la recherche en interaction avec un utilisateur est une approche qui permet de résoudre des requêtes à la sémantique complexe avec rapidité, sans pour autant nécessiter un haut niveau d'expertise utilisateur. Parmi les différents éléments intervenant dans la conception d'un système de recherche interactive, deux parties essentielles interviennent: l'indexation et la similarité entre les documents multimédia, et la gestion du processus interact

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Sungeelee, Vaynee. "Human-Machine Co-Learning : interactive curriculum generation for the acquisition of motor skills." Electronic Thesis or Diss., Sorbonne université, 2024. https://theses.hal.science/tel-04828514.

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L'acquisition de compétences motrices est le processus par lequel une personne est capable d'exécuter un mouvement avec plus de précision. Dans ce contexte, la pratique joue un rôle déterminant ; elle contribue à améliorer les performances de l'apprenant, mais n'y est pas toujours adapté. Un moyen de personnaliser l'apprentissage est de créer des séquences d'apprentissage qui conviennent à l'apprenant. Cependant, créer ces séquences manuellement demande du temps, ce qui rend cette démarche peu pratique. La génération automatique de séquences d'apprentissage peut remédier à ce problème. Les str

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Crochepierre, Laure. "Apprentissage automatique interactif pour les opérateurs du réseau électrique." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0112.

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Dans le contexte de la transition énergétique et de l'augmentation des interconnexions entre les réseaux de transport d'électricité en Europe, les opérateurs du réseau français doivent désormais faire face à davantage de fluctuations et des dynamiques nouvelles sur le réseau. Pour garantir la sûreté de ce réseau, les opérateurs s'appuient sur des logiciels informatiques permettant de réaliser des simulations, ou de suivre l'évolution d'indicateurs créés manuellement par des experts grâce à leur connaissance du fonctionnement du réseau. Le gestionnaire de réseau de transport d'électricité franç

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Lai, Hien Phuong. "Vers un système interactif de structuration des index pour une recherche par le contenu dans des grandes bases d'images." Phd thesis, Université de La Rochelle, 2013. http://tel.archives-ouvertes.fr/tel-00934842.

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Cette thèse s'inscrit dans la problématique de l'indexation et la recherche d'images par le contenu dans des bases d'images volumineuses. Les systèmes traditionnels de recherche d'images par le contenu se composent généralement de trois étapes: l'indexation, la structuration et la recherche. Dans le cadre de cette thèse, nous nous intéressons plus particulièrement à l'étape de structuration qui vise à organiser, dans une structure de données, les signatures visuelles des images extraites dans la phase d'indexation afin de faciliter, d'accélérer et d'améliorer les résultats de la recherche ulté

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Pace, Aaron J. "Guided Interactive Machine Learning." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1355.pdf.

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Krishna, Sooraj. "Modelling communicative behaviours for different roles of pedagogical agents." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS286.

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Les agents dans un environnement d'apprentissage peuvent avoir divers rôles et comportements sociaux qui peuvent influencer les objectifs et la motivation des apprenants de différentes manières. L'apprentissage autorégulé (SRL) est un cadre conceptuel complet qui englobe les aspects cognitifs, métacognitifs, comportementaux, motivationnels et affectifs de l'apprentissage et implique les processus de définition d'objectifs, de suivi des progrès, d'analyse des commentaires, d'ajustement des objectifs et des actions de l'apprenant. Dans cette thèse, nous présentons une interaction d'apprentissage

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Schild, Erwan. "De l’importance de valoriser l’expertise humaine dans l’annotation : application à la modélisation de textes en intentions à l’aide d’un clustering interactif." Electronic Thesis or Diss., Université de Lorraine, 2024. http://www.theses.fr/2024LORR0024.

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La tâche d'annotation, nécessaire à l'entraînement d'assistants conversationnels, fait habituellement appel à des experts du domaine à modéliser. Toutefois, l'annotation de données est connue pour être une tâche difficile en raison de sa complexité et sa subjectivité : elle nécessite par conséquent de solides compétences analytiques dans le but de modéliser les textes en intention de dialogue. De ce fait, la plupart des projets d'annotation choisissent de former les experts aux tâches d'analyse pour en faire des "super-experts". Dans cette thèse, nous avons plutôt décidé mettre l'accent sur le

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Georgiev, Nikolay. "Assisting physiotherapists by designing a system utilising Interactive Machine Learning." Thesis, Uppsala universitet, Institutionen för informatik och media, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447489.

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Millions of people throughout the world suffer from physical injuries and impairments and require physiotherapy to successfully recover. There are numerous obstacles in the way of having access to the necessary care – high costs, shortage of medical personnel and the need to travel to the appropriate medical facilities, something even more challenging during the Covid-19 pandemic. One approach to addressing this issue is to incorporate technology in the practice of physiotherapists, allowing them to help more patients. Using research through design, this thesis explores how interactive machine

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Kim, Been. "Interactive and interpretable machine learning models for human machine collaboration." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98680.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 135-143).<br>I envision a system that enables successful collaborations between humans and machine learning models by harnessing the relative strength to accomplish what neither can do alone. Machine learning techniques and humans have skills that complement each other - machine learning techniques are good at computation on data at the lowest level of granularity, whereas people are better at abstracting

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Sahoo, Shibashankar. "Soft machine : A pattern language for interacting with machine learning algorithms." Thesis, Umeå universitet, Designhögskolan vid Umeå universitet, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-182467.

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The computational nature of soft computing e.g. machine learning and AI systems have been hidden by seamless interfaces for almost two decades now. It has led to the loss of control, inability to explore, and adapt to needs and privacy at an individual level to social-technical problems on a global scale. I propose a soft machine - a set of cohesive design patterns or ‘seams’ to interact with everyday ‘black-box’ algorithms. Through participatory design and tangible sketching, I illustrate several interaction techniques to show how people can naturally control, explore, and adapt in-context al

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Lagerkvist, Love. "Neural Novelty — How Machine Learning Does Interactive Generative Literature." Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-21222.

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Every day, machine learning (ML) and artificial intelligence (AI) embeds itself further into domestic and industrial technologies. Interaction de- signers have historically struggled to engage directly with the subject, facing a shortage of appropriate methods and abstractions. There is a need to find ways though which interaction design practitioners might integrate ML into their work, in order to democratize and diversify the field. This thesis proposes a mode of inquiry that considers the inter- active qualities of what machine learning does, as opposed the tech- nical specifications of wha

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Gogia, Sumit. "Insight : interactive machine learning for complex graphics selection." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106021.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 89-91).<br>Modern vector graphics editors support the creation of a wonderful variety of complex designs and artwork. Users produce highly realistic illustrations, stylized representational art, even nuanced data visualizati

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Bouillon, Manuel. "Apprentissage actif en-ligne d'un classifieur évolutif, application à la reconnaissance de commandes gestuelles." Thesis, Rennes, INSA, 2016. http://www.theses.fr/2016ISAR0019/document.

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L'utilisation de commandes gestuelles est une nouvelle méthode d'interaction sur interface tactile. Une bonne méthode pour faciliter la mémorisation de ces commandes gestuelles est de laisser l'utilisateur les personnaliser. Ce contexte applicatif induit une situation d'apprentissage croisé, où l'utilisateur doit mémoriser le jeu de symboles elle système doit apprendre à reconnaître les différents symboles. Cela implique un certain nombre de contraintes, à la fois sur le système de reconnaissance de symboles ct sur le système de supervision de son apprentissage. Il faut par exemple que le clas

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Md, Noor Mohammad Faizuddin. "Machine learning techniques for implicit interaction using mobile sensors." Thesis, University of Glasgow, 2016. http://theses.gla.ac.uk/7723/.

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Interactions in mobile devices normally happen in an explicit manner, which means that they are initiated by the users. Yet, users are typically unaware that they also interact implicitly with their devices. For instance, our hand pose changes naturally when we type text messages. Whilst the touchscreen captures finger touches, hand movements during this interaction however are unused. If this implicit hand movement is observed, it can be used as additional information to support or to enhance the users’ text entry experience. This thesis investigates how implicit sensing can be used to improv

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Turner, Jonathan Milton. "Obstacle avoidance and path traversal using interactive machine learning /." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1905.pdf.

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Wood, David K. "Learning from Gross Motion Observations of Human-Machine Interaction." Thesis, The University of Sydney, 2011. https://hdl.handle.net/2123/29223.

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This thesis discusses the problems inherent in the modelling and classification of human interactions with robots using gross motions observations. Contributions to this field are one approach by which robots can be made socially aware, at a low enough cost for the commercialisation of such systems to be viable. In general, it cheaper and simpler both in terms of sensing requirements and computational power to determine the position of a person participating in an interaction than to attempt to perform more advanced operations such as face detection and recognition, gaze tracking or ges

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Turner, Jonathan M. "Obstacle Avoidance and Path Traversal Using Interactive Machine Learning." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/1006.

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Recently there has been a growing interest in using robots in activities that are dangerous or cost prohibitive for humans to do. Such activities include military uses and space exploration. While robotic hardware is often capable of being used in these types of situations, the ability of human operators to control robots in an effective manner is often limited. This deficiency is often related to the control interface of the robot and the level of autonomy that control system affords the human operator. This thesis describes a robot control system, called the safe/unsafe system, which gives a

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Gustafson, Jonas. "Using Machine Learning to Identify Potential Problem Gamblers." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-163640.

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In modern casinos, personnel exist to advise, or in some cases, order individuals to stop gambling if they are found to be gambling in a destructive way, but what about online gamblers? This thesis evaluated the possibility of using machine learning as a supplement for personnel in real casinos when gambling online. This was done through supervised learning or more specifically, a decision tree algorithm called CART. Studies showed that the majority of problem gamblers would find it helpful to have their behavioral patterns collected to be able to identify their risk of becoming a problem gamb

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Chen, Si. "Active Learning Under Limited Interaction with Data Labeler." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104894.

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Active learning (AL) aims at reducing labeling effort by identifying the most valuable unlabeled data points from a large pool. Traditional AL frameworks have two limitations: First, they perform data selection in a multi-round manner, which is time-consuming and impractical. Second, they usually assume that there are a small amount of labeled data points available in the same domain as the data in the unlabeled pool. In this thesis, we initiate the study of one-round active learning to solve the first issue. We propose DULO, a general framework for one-round setting based on the notion of

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Holmberg, Lars. "Human In Command Machine Learning." Licentiate thesis, Malmö universitet, Malmö högskola, Institutionen för datavetenskap och medieteknik (DVMT), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-42576.

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Machine Learning (ML) and Artificial Intelligence (AI) impact many aspects of human life, from recommending a significant other to assist the search for extraterrestrial life. The area develops rapidly and exiting unexplored design spaces are constantly laid bare. The focus in this work is one of these areas; ML systems where decisions concerning ML model training, usage and selection of target domain lay in the hands of domain experts. This work is then on ML systems that function as a tool that augments and/or enhance human capabilities. The approach presented is denoted Human In Command ML

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Alcoverro, Vidal Marcel. "Stochastic optimization and interactive machine learning for human motion analysis." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/285337.

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The analysis of human motion from visual data is a central issue in the computer vision research community as it enables a wide range of applications and it still remains a challenging problem when dealing with unconstrained scenarios and general conditions. Human motion analysis is used in the entertainment industry for movies or videogame production, in medical applications for rehabilitation or biomechanical studies. It is also used for human computer interaction in any kind of environment, and moreover, it is used for big data analysis from social networks such as Youtube or Flickr, to men

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Patel, Vedang Vikrambhai. "Reduced Order Modeling For Fluid Structure Interaction Using Machine Learning." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1619276050317241.

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Xia, Guangyu. "Expressive Collaborative Music Performance via Machine Learning." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/784.

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Techniques of Artificial Intelligence and Human-Computer Interaction have empowered computer music systems with the ability to perform with humans via a wide spectrum of applications. However, musical interaction between humans and machines is still far less musical than the interaction between humans since most systems lack any representation or capability of musical expression. This thesis contributes various techniques, especially machine-learning algorithms, to create artificial musicians that perform expressively and collaboratively with humans. The current system focuses on three aspects

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Willman, Martin. "Machine Learning to identify cheaters in online games." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-170973.

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Cheating in online games is a problem both on the esport stage and in the gaming community. When a player cheats, the competitors do not compete on the same terms anymore and this becomes a major problem when high price pools are involved in online games. In this master thesis, a machine learning approach will be developed and tested to try to identify cheaters in the first-person shooter game Counter-Strike : Global Offensive. The thesis will also go through how the game Counter-Strike : Global Offensive works, give examples of anti-cheat softwares that exists, analyse different cheats in the

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Chen, Li. "Searching for significant feature interaction from biological data." Diss., Online access via UMI:, 2007.

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Charif, Omar. "Modelling and simulating individual's mobility : case study of Luxembourg and its greater region." Thesis, Compiègne, 2013. http://www.theses.fr/2013COMP2130.

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Dans le dernier siècle, le transport et en particulier l'utilisation des voitures privées a émergé comme une des sources principales d'émission de CO2 (deuxième derrière la production d'énergie). Plusieurs villes dans le monde ont mis en place des stratégies pour faire face à ce phénomène afin de limiter les impacts environnementaux néfastes. Certaines stratégies n'ont pas pu atteindre leur objectif, voire ils ont eu des réactions négatives auprès des individus. Le but de cette thèse de doctorat consiste à proposer une méthodologie et une plateforme pour la modélisation et la simulation du sys

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Stenström, Albin. "Clicking using the eyes, a machine learning approach." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121834.

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This master thesis report describes the work of evaluating the approach of using an eye-tracker and machine learning to generate an interaction model for clicks. In the study, recordings were done from 10 participants using a quiz application, and machine learning was then applied. Models were created with varying quality from a machine learning view, although most models did not work well for interaction. One model was created that enable correct interaction 80\% of the time, although the specific circumstances for success were not identified. The conclusion of the thesis is that the approach

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Riviere, Jean-Philippe. "Capturing traces of the dance learning process." Electronic Thesis or Diss., université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG054.

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Cette thèse porte sur la conception d’outils interactifs pour comprendre et faciliter l’apprentissage de la danse à partir de vidéos. Les processus d’apprentissage des danseurs représentent une source d’informations riches pour les chercheurs qui s’intéressent à la conception de systèmes soutenant l’apprentissage moteur. En effet, les danseurs experts réutilisent un large éventail de compétences qu’ils ont appris. Cependant, ces compétences sont en partie le résultat de connaissances implicites et incarnées,qui sont difficilement exprimables et verbalisables par un individu.Dans cette thèse, j

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Anderson, Corin R. "A machine learning approach to Web personalization /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/6875.

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Dias, Pedro Ricardo Gomes. "Recommending media content based on machine learning methods." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/6581.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática<br>Information is nowadays made available and consumed faster than ever before. This information technology generation has access to a tremendous deal of data and is left with the heavy burden of choosing what is relevant. With the increasing growth of media sources, the amount of content made available to users has become overwhelming and in need to be managed. Recommender systems emerged with the purpose of providing personalized and meaningful content recommendations based on users’ preferences and usage history. Due

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Harbert, Christopher W. Shang Yi. "An application of machine learning techniques to interactive, constraint-based search." Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/4324.

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Thesis (M.S.)--University of Missouri-Columbia, 2005.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (December 12, 2006) Includes bibliographical references.

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Parikh, Neena (Neena S. ). "Interactive tools for fantasy football analytics and predictions using machine learning." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100687.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 83-84).<br>The focus of this project is multifaceted: we aim to construct robust predictive models to project the performance of individual football players, and we plan to integrate these projections into a web-based application for in-depth fantasy football analytics. Most existing statistical tools for the NFL are limited to the use of macro-level data; this research looks to explore st

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Westphal, Florian. "Efficient Document Image Binarization using Heterogeneous Computing and Interactive Machine Learning." Licentiate thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16797.

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Large collections of historical document images have been collected by companies and government institutions for decades. More recently, these collections have been made available to a larger public via the Internet. However, to make accessing them truly useful, the contained images need to be made readable and searchable. One step in that direction is document image binarization, the separation of text foreground from page background. This separation makes the text shown in the document images easier to process by humans and other image processing algorithms alike. While reasonably well worki

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Yu, Guoqiang. "Machine Learning to Interrogate High-throughput Genomic Data: Theory and Applications." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/28980.

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The missing heritability in genome-wide association studies (GWAS) is an intriguing open scientific problem which has attracted great recent interest. The interaction effects among risk factors, both genetic and environmental, are hypothesized to be one of the main missing heritability sources. Moreover, detection of multilocus interaction effect may also have great implications for revealing disease/biological mechanisms, for accurate risk prediction, personalized clinical management, and targeted drug design. However, current analysis of GWAS largely ignores interaction effects, partly due t

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Delaunay, Julien. "Explainability for machine learning models : from data adaptability to user perception." Electronic Thesis or Diss., Université de Rennes (2023-....), 2023. http://www.theses.fr/2023URENS076.

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Cette thèse se concentre sur la génération d'explications locales pour les modèles de machine learning déjà déployés, en recherchant les conditions optimales pour des explications pertinentes, prenant en compte à la fois les données et les besoins de l'utilisateur. L'objectif principal est de développer des méthodes produisant des explications pour n'importe quel modèle de prédiction, tout en veillant à ce que ces explications demeurent à la fois fidèles au modèle sous-jacent et compréhensibles par les utilisateurs qui les reçoivent. La thèse est divisée en deux parties. Dans la première, on a

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Sullivan, Patrick Ryan. "ALJI: Active Listening Journal Interaction." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/95207.

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Depression is a crippling burden on a great many people, and it is often well hidden. Mental health professionals are able to treat depression, but the general public is not well versed in recognizing depression symptoms or assessing their own mental health. Active Listening Journal Interaction (ALJI) is a computer program that seeks to identify and refer people suffering with depression to mental health support services. It does this through analyzing personal journal entries using machine learning, and then privately responding to the author with proper guidance. In this thesis, we focus

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Vitt, Artur. "Machine Learning in DigitalTelerehabilitation : Telerehabilitation system based on kinect." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-70048.

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The healthcare as a service is always under pressure and is in great demand. Despiteliving in a developed world with access to cars, trains, busses and other transportationmeans, sometimes accessing healthcare can be troublesome and costly. Thecontinuous technological progress provides new means to provide different kind ofservices, healthcare included. One way of putting technology into good use in fieldof healthcare is remote rehabilitation.Remote rehabilitation is a matter of delivering physiotherapy on a distance. Theuse of remote rehabilitation potentially reduces waiting time for treatme

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Agarwal, Ankur. "Machine Learning for Image Based Motion Capture." Phd thesis, Grenoble INPG, 2006. http://tel.archives-ouvertes.fr/tel-00390301.

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Image based motion capture is a problem that has recently gained a lot of attention in the domain of understanding human motion in computer vision. The problem involves estimating the 3D configurations of a human body from a set of images and has applications that include human computer interaction, smart surveillance, video analysis and animation. This thesis takes a machine learning based approach to reconstructing 3D pose and motion from monocular images or video. It makes use of a collection of images and motion capture data to derive mathematical models that allow the recovery of full bod

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Letard, Vincent. "Apprentissage incrémental de modèles de domaines par interaction dialogique." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS100/document.

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L'intelligence artificielle est la discipline de recherche d'imitation ou de remplacement de fonctions cognitives humaines. À ce titre, l'une de ses branches s'inscrit dans l'automatisation progressive du processus de programmation. Il s'agit alors de transférer de l'intelligence ou, à défaut de définition, de transférer de la charge cognitive depuis l'humain vers le système, qu'il soit autonome ou guidé par l'utilisateur. Dans le cadre de cette thèse, nous considérons les conditions de l'évolution depuis un système guidé par son utilisateur vers un système autonome, en nous appuyant sur une a

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Stoffel, Florian [Verfasser]. "Transparency in Interactive Feature-based Machine Learning : Challenges and Solutions / Florian Stoffel." Konstanz : Bibliothek der Universität Konstanz, 2018. http://d-nb.info/1173616314/34.

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Dondelinger, Frank. "Machine learning approach to reconstructing signalling pathways and interaction networks in biology." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/7850.

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In this doctoral thesis, I present my research into applying machine learning techniques for reconstructing species interaction networks in ecology, reconstructing molecular signalling pathways and gene regulatory networks in systems biology, and inferring parameters in ordinary differential equation (ODE) models of signalling pathways. Together, the methods I have developed for these applications demonstrate the usefulness of machine learning for reconstructing networks and inferring network parameters from data. The thesis consists of three parts. The first part is a detailed comparison of a

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Cai, Bingjing. "Machine learning approaches for extracting protein complexes from protein-protein interaction networks." Thesis, Ulster University, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603536.

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Recent advances in molecular biology have led to the accumulation of large amounts of data on Protein-Protein Interaction (PPI) networks in different species, such as yeast and humans. Due to the inherent complexity, analysing such volumes of data to extract knowledge, such as protein complexes or regulatory pathways, represents not only an enormous challenge but also a great opportunity. This Thesis explores the application of machine learning approaches to detecting protein complexes from PPI networks obtained by Tandem Affinity Purification/Mass Spectrometry (TAP-MS) experiments. TAP-MS PPI

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Sarigul, Erol. "Interactive Machine Learning for Refinement and Analysis of Segmented CT/MRI Images." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/25954.

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This dissertation concerns the development of an interactive machine learning method for refinement and analysis of segmented computed tomography (CT) images. This method uses higher-level domain-dependent knowledge to improve initial image segmentation results. A knowledge-based refinement and analysis system requires the formulation of domain knowledge. A serious problem faced by knowledge-based system designers is the knowledge acquisition bottleneck. Knowledge acquisition is very challenging and an active research topic in the field of machine learning and artificial intelligence. Common

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Iqbal, Sumaiya. "Machine Learning based Protein Sequence to (un)Structure Mapping and Interaction Prediction." ScholarWorks@UNO, 2017. http://scholarworks.uno.edu/td/2379.

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Proteins are the fundamental macromolecules within a cell that carry out most of the biological functions. The computational study of protein structure and its functions, using machine learning and data analytics, is elemental in advancing the life-science research due to the fast-growing biological data and the extensive complexities involved in their analyses towards discovering meaningful insights. Mapping of protein’s primary sequence is not only limited to its structure, we extend that to its disordered component known as Intrinsically Disordered Proteins or Regions in proteins (IDPs/IDRs

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Wang, Jianxiong. "A machine learning system for understanding appraisal in design documents." Thesis, The University of Sydney, 2009. https://hdl.handle.net/2123/28237.

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This thesis describes a machine learning system for understanding appraisal in design documents. In linguistics, analysis of attitudes expressed in text is known as appraisal, which is the writer's subjective attitude (i.e., the opinion, sentiment or attitude expressed) toward the semantic meaning. Semantic orientation is the aspect of appraisal that expresses the positive or negative stance of the author to the semantic meaning. Computational linguistics methods have been introduced into the area of understanding appraisal. In computational linguistics, the analysis of appraisal is know

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Sanchez, Téo. "Interactive Machine Teaching with and for Novices." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG055.

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Les algorithmes d'apprentissage machine déployés dans la société ou la technologie offrent généralement aux utilisateurs aucune prise sur la manière dont les modèles d'apprentissage sont optimisés à partir des données. Seuls les experts conçoivent, analysent et optimisent les algorithmes d'apprentissage automatique. À l'intersection de l'Interaction Humain-Machine (IHM) et de l'apprentissage machine, le domaine de l'apprentissage automatique interactif vise à intégrer l'apprentissage automatique dans des pratiques existantes. L'enseignement machine interactif (Interactive Machine Teaching), en

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Lynch, Paul Kieran. "The generation of knowledge based systems for interactive nonlinear constrained optimisation." Thesis, Queen's University Belfast, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388221.

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Billewicz, Agnieszka. "Study of a relationship. Designerly explorations of machine learning algorithms." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-22593.

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Study of a relationship is a 10-week Research by Design project that explores the space of intersection between Design and Machine Learning. It is a series of design engagements and experiments, heavily grounded in the present time and simple technology, that produces a semi-abstract knowledge on relationship that can be established between human and Machine Learning artefacts. This research strives to propose an alternative designerly approach towards Machine Learning, one that would promote evoking positive emotions, usage for personal purposes and understanding of basic principles behind te

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Akrour, Riad. "Robust Preference Learning-based Reinforcement Learning." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112236/document.

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Les contributions de la thèse sont centrées sur la prise de décisions séquentielles et plus spécialement sur l'Apprentissage par Renforcement (AR). Prenant sa source de l'apprentissage statistique au même titre que l'apprentissage supervisé et non-supervisé, l'AR a gagné en popularité ces deux dernières décennies en raisons de percées aussi bien applicatives que théoriques. L'AR suppose que l'agent (apprenant) ainsi que son environnement suivent un processus de décision stochastique Markovien sur un espace d'états et d'actions. Le processus est dit de décision parce que l'agent est appelé à ch

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