Relevant bibliographies by topics / Machine Learning(ML) Techniques / Dissertations / Theses
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Dissertations / Theses on the topic 'Machine Learning(ML) Techniques'

Author: Grafiati
Published: 5 June 2025
Last updated: 16 July 2025

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1

Delestrac, Paul. "Advanced Profiling Techniques For Evaluating GPU Computing Efficiency Executing ML Applications." Electronic Thesis or Diss., Université de Montpellier (2022-....), 2024. http://www.theses.fr/2024UMONS014.

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L'augmentation en complexité des applications d'Intelligence Artificielle (IA) entraîne une demande accrue en puissance de calcul et en énergie pour entraîner et exécuter des modèles d'apprentissage automatique (ML). Les processeurs graphiques (GPU), forts d'architectures améliorées (e.g., ajout de cœurs dédiés à l'IA en 2017), sont devenus le système de prédilection pour de telles tâches. Concevoir des systèmes plus efficients pour l'IA n'est possible qu'avec une connaissance approfondie des limites des systèmes existants, où matériel et logiciel sont étroitement couplés. Mais l'abstraction d
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Garg, Anushka. "Comparing Machine Learning Algorithms and Feature Selection Techniques to Predict Undesired Behavior in Business Processesand Study of Auto ML Frameworks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-285559.

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In recent years, the scope of Machine Learning algorithms and its techniques are taking up a notch in every industry (for example, recommendation systems, user behavior analytics, financial applications and many more). In practice, they play an important role in utilizing the power of the vast data we currently generate on a daily basis in our digital world.In this study, we present a comprehensive comparison of different supervised Machine Learning algorithms and feature selection techniques to build a best predictive model as an output. Thus, this predictive model helps companies predict unw
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Liu, Siyang. "Efficient machine learning techniques for indoor localization in wireless communication systems." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST188.

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Avec le développement rapide de l'Internet des objets (IoT), le besoin de services de localisation en intérieur, tels que la gestion des actifs, la navigation et le suivi, a également augmenté au fil du temps. Pour la localisation indoor, les systèmes de navigation par satellite tels que le GPS ont un usage limité par l'absence de visibilité directe avec les satellites.Diverses solutions ont été proposées pour la localisation en intérieur, telles que la trilatération, la triangulation et la navigation à l'estime, mais leurs performances sont limitées par les conditions du canal intérieur, tell
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MASTRO, PIETRO. "Innovative Techniques for the Retrieval of Earth’s Surface and Atmosphere Geophysical Parameters: Spaceborne Infrared/Microwave Combined Analyses." Doctoral thesis, Università degli studi della Basilicata, 2023. https://hdl.handle.net/11563/162986.

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With the advent of the first satellites for Earth Observation: Landsat-1 in July 1972 and ERS-1 in May 1991, the discipline of environmental remote sensing has become, over time, increasingly fundamental for the study of phenomena characterizing the planet Earth. The goal of environmental remote sensing is to perform detailed analyses and to monitor the temporal evolution of different physical phenomena, exploiting the mechanisms of interaction between the objects that are present in an observed scene and the electromagnetic radiation detected by sensors, placed at a distance from the scene, o
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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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6

Nangalia, V. "ML-EWS - Machine Learning Early Warning System : the application of machine learning to predict in-hospital patient deterioration." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/1565193/.

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Preventing hospitalised patients from suffering adverse event (AEs) (unexpected cardiac, arrest, intensive care unit admission, surgery or death) is a priority in healthcare. Almost 50% of these AEs, caused by mistakes/poor standards of care, are thought to be preventable. The identification and referral of a patient at risk of an AE to a dedicated rapid response team is a key mechanism for their reduction. Focussing on variables that are routinely collected and electronically stored (blood test data, and administrative data: demographics, date and method of admission, and co-morbidities), alo
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Mattsson, Fredrik, and Anton Gustafsson. "Optimize Ranking System With Machine Learning." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-37431.

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This thesis investigates how recommendation systems has been used and can be used with the help of different machine learning algorithms. Algorithms used and presented are decision tree, random forest and singular-value decomposition(SVD). Together with Tingstad, we have tried to implement the SVD function on their recommendation engine in order to enhance the recommendation given. A trivial presentation on how the algorithms work. General information about machine learning and how we tried to implement it with Tingstad’s data. Implementations with Netflix’s and Movielens open-source dataset w
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8

Bozdemir, Beyza. "Privacy-preserving machine learning techniques." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS323.

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L'apprentissage automatique en tant que service (MLaaS) fait référence à un service qui permet aux entreprises de déléguer leurs tâches d'apprentissage automatique à un ou plusieurs serveurs puissants, à savoir des serveurs cloud. Néanmoins, les entreprises sont confrontées à des défis importants pour garantir la confidentialité des données et le respect des réglementations en matière de protection des données. L'exécution de tâches d'apprentissage automatique sur des données sensibles nécessite la conception de nouveaux protocoles garantissant la confidentialité des données pour les technique
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9

John, Meenu Mary. "Design Methods and Processes for ML/DL models." Licentiate thesis, Malmö universitet, Institutionen för datavetenskap och medieteknik (DVMT), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-45026.

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Context: With the advent of Machine Learning (ML) and especially Deep Learning (DL) technology, companies are increasingly using Artificial Intelligence (AI) in systems, along with electronics and software. Nevertheless, the end-to-end process of developing, deploying and evolving ML and DL models in companies brings some challenges related to the design and scaling of these models. For example, access to and availability of data is often challenging, and activities such as collecting, cleaning, preprocessing, and storing data, as well as training, deploying and monitoring the model(s) are com
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10

Tabell, Johnsson Marco, and Ala Jafar. "Efficiency Comparison Between Curriculum Reinforcement Learning & Reinforcement Learning Using ML-Agents." Thesis, Blekinge Tekniska Högskola, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20218.

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11

Kakadost, Naser, and Charif Ramadan. "Empirisk undersökning av ML strategier vid prediktion av cykelflöden baserad på cykeldata och veckodagar." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20168.

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Detta arbete fokuserar på prediktion av cykeltrafik under en månad på en given gata i Malmö med hjälp av maskininlärning. Algoritmen som används är Python-implementering av Stödvektormaskin (Support Vector Machine) från Scikit . Data som används är antalet cyklister/dag under 2006-2013 från en cykel-barometer som är placerad på Kaptensgatan i Malmö. Barometerns funktion är att räkna antalet cyklar som passerar samt registrera tiden. I vår studie undersöker vi hur precision av prediktionen av antalet cyklister varje dag under fyra veckor i oktober 2013, mätt med metoderna RMSE och MAPE, beror a
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12

Gustafsson, Sebastian. "Interpretable serious event forecasting using machine learning and SHAP." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-444363.

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Accurate forecasts are vital in multiple areas of economic, scientific, commercial, and industrial activity. There are few previous studies on using forecasting methods for predicting serious events. This thesis set out to investigate two things, firstly whether machine learning models could be applied to the objective of forecasting serious events. Secondly, if the models could be made interpretable. Given these objectives, the approach was to formulate two forecasting tasks for the models and then use the Python framework SHAP to make them interpretable. The first task was to predict if a se
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13

Barnabò, Andrea. "Machine learning techniques for mammography applications." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.

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During this work we will use machine learning and deep learning techniques in order to face up to some medical problems where they can play a basic role. In particular we will apply these algorithms to some mammography issues. The thesis presents three main experiments that are described below. The first one consists of a classification between nipples and non-nipples images. In this part of the work we will build a dataset composed by images belonging to these two classes. The main purpose here will be to build a classifier able to distinguish between nipple and non-nipple images. Several mac
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14

Mona, Dadoun. "Predicting Fashion using Machine Learning techniques." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210413.

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On a high-level perspective, fashion is an art defined by fash- ion stylists and designers to express their thoughts and opinions. Lately, fashion have also been defined by digital publishers such as bloggers and online magazines. These digital publishers create fashion by curating and publishing content that is hopefully rel- evant and of high quality for their readers. Within this master’s thesis, fashion forecasting was investigated by applying supervised machine learning techniques. The problem was investigated by training classification learning models on a real world historical fashion d
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15

Rogers, Simon David. "Machine learning techniques for microarray analysis." Thesis, University of Bristol, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409426.

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16

Boyapati, Sai Nikhil, and Ramesh Mummidi. "Predicting sales using Machine Learning Techniques." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20237.

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17

Caceres, Carlos Antonio. "Machine Learning Techniques for Gesture Recognition." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/52556.

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Classification of human movement is a large field of interest to Human-Machine Interface researchers. The reason for this lies in the large emphasis humans place on gestures while communicating with each other and while interacting with machines. Such gestures can be digitized in a number of ways, including both passive methods, such as cameras, and active methods, such as wearable sensors. While passive methods might be the ideal, they are not always feasible, especially when dealing in unstructured environments. Instead, wearable sensors have gained interest as a method of gesture classifica
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18

Sammaritani, Gloria. "Google BigQuery ML. Analisi comparativa di un nuovo framework per il Machine Learning." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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La crescita esponenziale nella digitalizzazione dei processi, lo sviluppo dei canali digitali e laconseguente crescita del volume e della variet`a dei dati operativi, unitamente e al miglioramentodelle tecnologie e capacit`a computazionali ha permesso di registrare notevoli progressi in ambitoMachine Learning. Le tecniche sviluppate all’interno di questo campo sono ora in grado dianalizzare e apprendere da enormi quantit`a di esempi del mondo reale. Il numero di algoritmi diMachine Learning `e ampio e in crescita cos`ı come le loro implementazioni attraverso frameworke librerie. Lo sviluppo
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19

Schoenfeld, Brandon J. "Metalearning by Exploiting Granular Machine Learning Pipeline Metadata." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8730.

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Automatic machine learning (AutoML) systems have been shown to perform better when they use metamodels trained offline. Existing offline metalearning approaches treat ML models as black boxes. However, modern ML models often compose multiple ML algorithms into ML pipelines. We expand previous metalearning work on estimating the performance and ranking of ML models by exploiting the metadata about which ML algorithms are used in a given pipeline. We propose a dynamically assembled neural network with the potential to model arbitrary DAG structures. We compare our proposed metamodel against reas
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Hellborg, Per. "Optimering av datamängder med Machine learning : En studie om Machine learning och Internet of Things." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-13747.

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This report is about how an Internet of Things (IoT) optimization can be done with Machine learning (ML). The IoT- devices in this report are sensors in containers that read how full the containers are. The report contains a case from Sogeti. Were a client can use this optimization to get better routes for their garbage truck, with this solution the garbage trucks will only go to full containers and be able to skip empty or close to empty containers. This will result in less fuel costs and a better environment. This solution can be used for every industry that needs a route optimization. To do
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21

Jernbäcker, Carl, and Shahrivar Pojan. "Predicting movie success using machine learning techniques." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208506.

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The area of creating predictive models using machine learning has increased in size in recent years. The market for movies is still big with hundreds of new movies created every year. The purpose of this report is to investigate whether it is possible to classify movie rating and box office revenue with metadata available before release. This was done by building a classification model with metadata obtained from the internet such as, budget and what actors are involved, etc. This study managed to correctly predict what rating a movie would have about 82% of the time using the technique with t
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22

Tan, Feng. "Improving Feature Selection Techniques for Machine Learning." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/cs_diss/27.

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As a commonly used technique in data preprocessing for machine learning, feature selection identifies important features and removes irrelevant, redundant or noise features to reduce the dimensionality of feature space. It improves efficiency, accuracy and comprehensibility of the models built by learning algorithms. Feature selection techniques have been widely employed in a variety of applications, such as genomic analysis, information retrieval, and text categorization. Researchers have introduced many feature selection algorithms with different selection criteria. However, it has been disc
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23

Long, Shun. "Adaptive Java optimisation using machine learning techniques." Thesis, University of Edinburgh, 2004. http://hdl.handle.net/1842/567.

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There is a continuing demand for higher performance, particularly in the area of scientific and engineering computation. In order to achieve high performance in the context of frequent hardware upgrading, software must be adaptable for portable performance. What is required is an optimising compiler that evolves and adapts itself to environmental change without sacrificing performance. Java has emerged as a dominant programming language widely used in a variety of application areas. However, its architectural independant design means that it is frequently unable to deliver high performance esp
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24

Isaksson, Emil, and Conde Mikael Karpe. "Solar Power Forecasting with Machine Learning Techniques." Thesis, KTH, Matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229065.

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The increased competitiveness of solar PV panels as a renewable energy source has increased the number of PV panel installations in recent years. In the meantime, higher availability of data and computational power have enabled machine learning algorithms to perform improved predictions. As the need to predict solar PV energy output is essential for many actors in the energy industry, machine learning and time series models can be employed towards this end. In this study, a comparison of different machine learning techniques and time series models is performed across five different sites in Sw
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25

Chi, Yuan. "Machine learning techniques for high dimensional data." Thesis, University of Liverpool, 2015. http://livrepository.liverpool.ac.uk/2033319/.

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This thesis presents data processing techniques for three different but related application areas: embedding learning for classification, fusion of low bit depth images and 3D reconstruction from 2D images. For embedding learning for classification, a novel manifold embedding method is proposed for the automated processing of large, varied data sets. The method is based on binary classification, where the embeddings are constructed so as to determine one or more unique features for each class individually from a given dataset. The proposed method is applied to examples of multiclass classifica
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Botsch, Michael-Felix. "Machine learning techniques for time series classification." Göttingen Cuvillier, 2009. http://d-nb.info/994721455/04.

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27

Poggi, Matteo <1990&gt. "Machine Learning techniques applied to stereo vision." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amsdottorato.unibo.it/8444/1/thesis.pdf.

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Stereo is a popular technique enabling fast and dense depth estimation from two or more images. Its success is mainly due to its easiness of deployment, requiring only a couple or multiple synchronized image sensors, accurately calibrated to solve the matching problem between pixels on one of the images (named reference) and the other (named target). The absence of active technologies (e.g. pattern projection, laser scanners etc..) make this solution deployable on almost every scenario. Despite the wide literature concerning stereo, it still represents an open problem because of very challen
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28

Cahill, Jaspar. "Machine learning techniques to improve software quality." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/41730/1/Jaspar_Cahill_Thesis.pdf.

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A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are
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CAZZATO, STEFANIA. "Machine Learning Techniques Applied to Telecommunication Data." Doctoral thesis, Università degli studi di Genova, 2019. http://hdl.handle.net/11567/942536.

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CATTANEO, DANIELE. "Machine Learning Techniques for Urban Vehicle Localization." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2020. http://hdl.handle.net/10281/263540.

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In questa tesi presento il mio lavoro di dottorato, che ha riguardato la localizzazione di un veicolo stradale in ambito urbano. In particolare, ho fatto uso di tecniche di Machine Learning per l'elaborazione delle immagini provenienti dalle camere a bordo di un veicolo. I sistemi sviluppati hanno lo scopo di produrre una stima della posa del veicolo e quindi, nel caso di deep neural networks, si tratta di reti che effettuano una pose regression. Al meglio della mia conoscenza, alcuni dei miei sviluppi sono i primi in letteratura in grado di effettuare visual pose regression basandosi su mappe
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31

Shahbazi, Arzhang. "Machine Learning Techniques for UAV-assisted Networks." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG076.

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L'objectif principal de cette thèse est la modélisation, l'évaluation des performances et l'optimisation au niveau du système des réseaux cellulaires de prochaine génération équipés de drones en utilisant l'intelligence artificielle. En outre, la technologie émergente de détection et de communication intégrées est étudiée pour être appliquée aux futurs réseaux sans fil des drones. En particulier, en s'appuyant sur la technique d'apprentissage par renforcement pour contrôler les actions des drones, cette thèse développe un ensemble de nouveaux cadres d'apprentissage automatique pour incorporer
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Nämerforslund, Tim. "Machine Learning Adversaries in Video Games : Using reinforcement learning in the Unity Engine to create compelling enemy characters." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42746.

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I och med att videospel blir mer avancerade, inte bara grafiskt utan också som konstform samt att dom erbjuder en mer inlevelsefull upplevelse, så kan det förväntas att spelen också ska erbjuda en större utmaning för att få spelaren bli ännu mer engagerad i spelet. Dagens spelare är vana vid fiender vars beteende styrs av tydliga mönster och regler, som beroende på situation agerar på ett förprogrammerat sätt och agerar utifrån förutsägbara mönster. Detta leder till en spelupplevelse där målet blir att klura ut det här mönstret och hitta ett sätt att överlista eller besegra det. Men tänk om det
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Nguyen, Thi Thu Thuy. "Advanced machine learning techniques for online and data stream learning." Thesis, Griffith University, 2019. http://hdl.handle.net/10072/386536.

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Big Data is the certain result of our knowledge-intensive world when practically everything is being monitored and measured. According to the 2014 report of the International Data Corporation (IDC), the amount of information created, captured or replicated had exceeded available storage for the first time in 2007. The digital universe is doubling in size every two years and will multiply 10-fold between 2013 and 2020 – from 4.4 trillion gigabytes to 44 trillion gigabytes. Besides the massive volume, the velocity of data is another concern as in our information society, very often data come in
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Mahfouz, Tarek Said. "Construction legal support for differing site conditions (DSC) through statistical modeling and machine learning (ML)." [Ames, Iowa : Iowa State University], 2009.

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Tugnoli, Riccardo. "MVA Calculation and Optimization with Machine Learning Techniques." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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In the last few years a new margin requirement, the Initial Margin, was introduced by both Central Counterparties for cleared derivatives and BCBS\&IOSCO for derivatives Over The Counter in order to reduce the counterparty credit risk when dealing derivatives. Besides, due to its segregation, the IM funding always represents a cost. Consequently, a pricing adjustment, called (Initial) Margin Valuation Adjustment, needs to be applied. Since the IM is based on a risk measure (i.e. Value at Risk or Expected Shortfall), the MVA calculation involves a nested Monte Carlo simulation, which is computa
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Ortiz, Pedro. "Machine learning techniques for persuasion dectection in conversation." Thesis, Monterey, California : Naval Postgraduate School, 2010. http://edocs.nps.edu/npspubs/scholarly/theses/2010/Jun/10Jun%5FOrtiz.pdf.

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Thesis (M.S. in Computer Science)--Naval Postgraduate School, June 2010.<br>Thesis Advisor(s): Martell, Craig H. ; Second Reader: Young, Joel D. "June 2010." Description based on title screen as viewed on July 16, 2010. Author(s) subject terms: Persuasion, conversation, machine learning, naive bayes, maximum entropy, support vector machine, Waco, David Koresh, negotiation, transcript, Cialdini. Includes bibliographical references (p. 105-107). Also available in print.
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Bodin, Erik. "Video content annotation automation using machine learning techniques." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-155751.

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Annotations describing semantic content within video material is essential for ecient search of such content, e.g. allowing for search engine queries to return only relevant segments of video clips within large content management systems. However, manual annotation of video material is a dull and time-consuming task, eectively lowering thequality and quantity of such annotations. In this rapport a system to automate most of the process is suggested. The system learns from video material with user-provided annotationsto infer annotations for new material automatically, without requiring any sys
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Yao, Jian. "Developing machine learning techniques for real world applications." Diss., Online access via UMI:, 2006.

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Matta, Durga Mahesh, and Meet Kumar Saraf. "Prediction of COVID-19 using Machine Learning Techniques." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20232.

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Background: Over the past 4-5 months, the Coronavirus has rapidly spread to all parts of the world. Research is continuing to find a cure for this disease while there is no exact reason for this outbreak. As the number of cases to test for Coronavirus is increasing rapidly day by day, it is impossible to test due to the time and cost factors. Over recent years, machine learning has turned very reliable in the medical field. Using machine learning to predict COVID-19 in patients will reduce the time delay for the results of the medical tests and modulate health workers to give proper medical tr
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Kothawade, Rohan Dilip. "Wine quality prediction model using machine learning techniques." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-20009.

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The quality of a wine is important for the consumers as well as the wine industry. The traditional (expert) way of measuring wine quality is time-consuming. Nowadays, machine learning models are important tools to replace human tasks. In this case, there are several features to predict the wine quality but the entire features will not be relevant for better prediction. So, our thesis work is focusing on what wine features are important to get the promising result. For the purposeof classification model and evaluation of the relevant features, we used three algorithms namely support vector mach
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Dabert, Geoffrey. "Application of Machine Learning techniques to Optimization algorithms." Thesis, KTH, Optimeringslära och systemteori, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-207471.

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Optimization problems have been immuned to any attempt of combination with machine learning until a decade ago but it is now an active research field. This thesis has studied the potential implementation of a machine learning heuristic to improve the resolution of the optimization scheduling problems based on a Constraint Programming solver. Some scheduling problems, known as N P -hard problems, suffer from large computational cost (large number of jobs to schedule) and consequent human effort (well-suited heuristics need to be derived). Moreover industrial scheduling problems obviously evolve
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Wang, Xing. "Human motion sequence characterization using machine learning techniques /." access full-text access abstract and table of contents, 2009. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?mphil-cs-b23750492f.pdf.

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Thesis (M.Phil.)--City University of Hong Kong, 2009.<br>"Submitted to Department of Computer Science in partial fulfillment of the requirements for the degree of Master of Philosophy." Includes bibliographical references (leaves [152]-163)
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Karlsson, Henrik. "Monitoring Vehicle Suspension Elements Using Machine Learning Techniques." Thesis, KTH, Spårfordon, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262916.

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Condition monitoring (CM) is widely used in industry, and there is a growing interest in applying CM on rail vehicle systems. Condition based maintenance has the possibility to increase system safety and availability while at the sametime reduce the total maintenance costs.This thesis investigates the feasibility of using condition monitoring of suspension element components, in this case dampers, in rail vehicles. There are different methods utilized to detect degradations, ranging from mathematicalmodelling of the system to pure "knowledge-based" methods, using only large amount of data to d
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Bányay, Dániel. "MLSurf : Surfer Motion Characterization Using Machine Learning Techniques." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264921.

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Wave surfing is a popular sport that requires minimal financial investment, while it can still be enjoyable from the very first attempt. At the same time, the demand for smart devices that enhance the experience of doing sports by analyzing and evaluating the activities is growing. For surf sport, there are some solutions that are able to collect statistics about activities being done during a surf session, but none of them is able to recognize specific maneuvers that are performed during wave riding. The goal of this Master Thesis is to improve a currently existing surf activity monitoring so
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ZINI, SIMONE. "Image Enhancement and Restoration using Machine Learning Techniques." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/378899.

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Le fotocamere digitali acquisiscono, manipolano e salvano in memoria informazioni elettronicamente tramite un sensore e unitá di calcolo integrate, rendendo la fotografia accessibile agli utenti finali i quali non necessitano di basi di conoscenza di chimica o delle specifiche operazioni meccaniche che erano necessarie per lo sviluppo con la fotografia analogica. Diversi tipi di degradazioni e artefatti possono affliggere le immagini acquisite tramite camere digitali, riducendo la fedeltà percepita delle immagini e rendendo piú difficili operazioni di visione artificiale che possono essere ope
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Chafik, Sanaa. "Machine learning techniques for content-based information retrieval." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLL008/document.

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Avec l’évolution des technologies numériques et la prolifération d'internet, la quantité d’information numérique a considérablement évolué. La recherche par similarité (ou recherche des plus proches voisins) est une problématique que plusieurs communautés de recherche ont tenté de résoudre. Les systèmes de recherche par le contenu de l’information constituent l’une des solutions prometteuses à ce problème. Ces systèmes sont composés essentiellement de trois unités fondamentales, une unité de représentation des données pour l’extraction des primitives, une unité d’indexation multidimensionnelle
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Chafik, Sanaa. "Machine learning techniques for content-based information retrieval." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLL008.

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Avec l’évolution des technologies numériques et la prolifération d'internet, la quantité d’information numérique a considérablement évolué. La recherche par similarité (ou recherche des plus proches voisins) est une problématique que plusieurs communautés de recherche ont tenté de résoudre. Les systèmes de recherche par le contenu de l’information constituent l’une des solutions prometteuses à ce problème. Ces systèmes sont composés essentiellement de trois unités fondamentales, une unité de représentation des données pour l’extraction des primitives, une unité d’indexation multidimensionnelle
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Boschin, Armand. "Machine learning techniques for automatic knowledge graph completion." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAT016.

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Un graphe de connaissances est un graphe orienté dont les nœuds sont des entités et les arêtes, typées par une relation, représentent des faits connus liant les entités. Ces graphes sont capables d'encoder une grande variété d'information mais leur construction et leur exploitation peut se révéler complexe. Historiquement, des méthodes symboliques ont permis d'extraire des règles d'interaction entre entités et relations, afin de corriger des anomalies ou de prédire des faits manquants. Plus récemment, des méthodes d'apprentissage de représentations vectorielles, ou plongements, ont tenté de ré
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Baban, Shaswar Tharwat Mohammed. "Context-aware cognitive radios learning from data using machine learning techniques." Thesis, King's College London (University of London), 2016. https://kclpure.kcl.ac.uk/portal/en/theses/contextaware-cognitive-radios-learning-from-data-using-machine-learning-techniques(674aef35-8640-41d2-97b2-922182f096cc).html.

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Wired or wireless, connectivity has been a vital commodity of life and more so recently in the realm of information age. Those who have access to faster, more reliable and more ubiquitous connectivity—put simply, those who are “better connected”—will have significant advantages in commerce, research and a host of other arenas. In regards to wireless communications, due to the explosion in demand for higher capacity networks, availability of free spectrum resources have become increasingly scarce. The UHF spectrum band in particular, due to its excellent electromagnetic properties, has been rep
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Atienza, Nicolas. "Towards Reliable ML : Leveraging Multi-Modal Representations, Information Bottleneck and Extreme Value Theory." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG025.

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Cette thèse de doctorat porte sur l'amélioration de la fiabilité de l'apprentissage automatique, en particulier pour les applications à forts enjeux. Les modèles d'apprentissage profond actuels, bien que très performants, restent difficiles à appréhender et à déployer de manière sûre en raison de leur opacité, de leur vulnérabilité aux attaques adverses, de leur sensibilité aux changements de distribution, et de leur inefficacité en contexte de données ou de ressources limitées. Pour surmonter ces limites, ce travail explore trois dimensions complémentaires : l'explicabilité, la robustesse et
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