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Dissertations / Theses on the topic 'Approaches to learning'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Potari, Despina. "Learning approaches in mathematics." Thesis, University of Edinburgh, 1987. http://hdl.handle.net/1842/12130.

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Hussein, Ahmed. "Deep learning based approaches for imitation learning." Thesis, Robert Gordon University, 2018. http://hdl.handle.net/10059/3117.

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Imitation learning refers to an agent's ability to mimic a desired behaviour by learning from observations. The field is rapidly gaining attention due to recent advances in computational and communication capabilities as well as rising demand for intelligent applications. The goal of imitation learning is to describe the desired behaviour by providing demonstrations rather than instructions. This enables agents to learn complex behaviours with general learning methods that require minimal task specific information. However, imitation learning faces many challenges. The objective of this thesis

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Effraimidis, Dimitros. "Computation approaches for continuous reinforcement learning problems." Thesis, University of Westminster, 2016. https://westminsterresearch.westminster.ac.uk/item/q0y82/computation-approaches-for-continuous-reinforcement-learning-problems.

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Optimisation theory is at the heart of any control process, where we seek to control the behaviour of a system through a set of actions. Linear control problems have been extensively studied, and optimal control laws have been identified. But the world around us is highly non-linear and unpredictable. For these dynamic systems, which don’t possess the nice mathematical properties of the linear counterpart, the classic control theory breaks and other methods have to be employed. But nature thrives by optimising non-linear and over-complicated systems. Evolutionary Computing (EC) methods exploit

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Chang, Yu-Han Ph D. Massachusetts Institute of Technology. "Approaches to multi-agent learning." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33932.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.<br>Includes bibliographical references (leaves 165-171).<br>Systems involving multiple autonomous entities are becoming more and more prominent. Sensor networks, teams of robotic vehicles, and software agents are just a few examples. In order to design these systems, we need methods that allow our agents to autonomously learn and adapt to the changing environments they find themselves in. This thesis explores ideas from game theory, online prediction, and reinforcement learning,

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Flaherty, Drew. "Artistic approaches to machine learning." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/200191/1/Drew_Flaherty_Thesis.pdf.

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This research is about how Artificial Intelligence and Machine Learning may impact creative practice. The thesis looks at various implementations and models related to the subject from different cultural and technical viewpoints. The project also provides experimental creative outcomes from my personal practice along with a qualitative study into attitudes and perspectives from other creative practitioners.

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Yu, Kai. "Statistical Learning Approaches to Information Filtering." Diss., lmu, 2004. http://nbn-resolving.de/urn:nbn:de:bvb:19-25120.

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Kashima, Hisashi. "Machine learning approaches for structured data." 京都大学 (Kyoto University), 2007. http://hdl.handle.net/2433/135953.

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Chen, Zhe Haykin Simon S. "Stochastic approaches for correlation-based learning." *McMaster only, 2004.

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9

Boots, Byron. "Spectral Approaches to Learning Predictive Representations." Research Showcase @ CMU, 2012. http://repository.cmu.edu/dissertations/131.

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A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must obtain an accurate environment model, and then plan to maximize reward. However, for complex domains, specifying a model by hand can be a time consuming process. This motivates an alternative approach: learning a model directly from observations. Unfortunately, learning algorithms often recover a model that is too inaccurate to support planning or too large and complex for planning to succeed; or, they require excessive prior domain knowledge

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Fu, I.-Ping P. "Student Approaches to Learning Chinese Vocabulary." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/25955.

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This research focuses on the strategies that native English speakers use as they learn to speak and write Chinese vocabulary words in the first year of an elementary Chinese class. The main research question was: what strategies do native English-speaking beginning learners of Chinese use to learn Chinese vocabulary words in their speaking and writing? The study was conducted at a medium-sized comprehensive university in the Southeastern U.S. The study drew from concepts and theories in second language acquisition and psycholinguistic studies. A random sampling of four students was select

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EL-Manzalawy, Yasser. "Machine learning approaches for epitope prediction." [Ames, Iowa : Iowa State University], 2008.

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12

Pellegrini, Giovanni. "Relational Learning approaches for Recommender Systems." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/318892.

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Learning on relational data is a relevant task in the machine learning community. Extracting information from structured data is a non-trivial task due to the combinatorial complexity of the domain and the necessity to construct methods that work on collections of values of different sizes rather than fixed representations. Relational data can naturally be interpreted as graphs, a class of flexible and expressive structures that can model data from diverse domains,from biology to social interactions. Graphs have been used in a huge variety of contexts, such as molecular modelling

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Pellegrini, Giovanni. "Relational Learning approaches for Recommender Systems." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/318892.

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Learning on relational data is a relevant task in the machine learning community. Extracting information from structured data is a non-trivial task due to the combinatorial complexity of the domain and the necessity to construct methods that work on collections of values of different sizes rather than fixed representations. Relational data can naturally be interpreted as graphs, a class of flexible and expressive structures that can model data from diverse domains,from biology to social interactions. Graphs have been used in a huge variety of contexts, such as molecular modelling

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AKBAR, MUHAMMAD USMAN. "Deep Learning Approaches Targeting Radiological Images." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1069387.

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Artificial Intelligence (AI) algorithms have remarkably improved their performance in the recent years in various domains, thanks to the introduction of deep learning approaches. Indeed they have shown a tremendous potential when solving tasks involving image analysisThe problem of deep learning is its requirement for huge datasets, nonetheless, DL approaches have proved to be helpful in the domain of medical imaging as well. Automated segmentation and classification in different biomedical tasks have proven to be faster and more cost effective. In this thesis we study deep learning approa

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Marsden-Huggins, John. "Towards an understanding of ESL students' approaches to learning: a study of conceptions of learning, perceptions of situational demands, learning approaches and learning outcomes." Doctoral thesis, University of Cape Town, 1994. http://hdl.handle.net/11427/15993.

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Includes bibliographical references.<br>An hypothesised relationship between levels of proficiency in English of ESL (English as a Second Language) students and the approaches to learning which they adopt, in situations in which English is the language of instruction, is the focus of this study. An attempt was made to identify the extent to which students, who are required to learn in a second language, adopt undesirable approaches to learning as a consequence of linguistic or cultural factors. Such students appear to adopt reproductive strategies to pass examinations and retain only isolated

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Del, Valle Rodrigo. "Online learning learner characteristics and their approaches to managing learning /." [Bloomington, Ind.] : Indiana University, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:3204535.

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Thesis (Ph.D.)--Indiana University, Dept. of Instructional Systems Technology of the School of Education, 2006.<br>Source: Dissertation Abstracts International, Volume: 67-01, Section: A, page: 0152. Adviser: Thomas M. Duffy. "Title from dissertation home page (viewed Jan. 8, 2007)."

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Katzenbach, Michael. "Individual Approaches in Rich Learning Situations Material-based Learning with Pinboards." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-80328.

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Active Approaches provide chances for individual, comprehension-oriented learning and can facilitate the acquirement of general mathematical competencies. Using the example of pinboards, which were developed for different areas of the secondary level, workshop participants experience, discuss and further develop learning tasks, which can be used for free activities, for material based concept formation, for coping with heterogeneity, for intelligent exercises, as tool for the presentation of students’ work and as basis for games. The material also allows some continuous movements and can thus

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Dalton-Brits, E., and M. Viljoen. "Personality traits and learning approaches : are they influencing the learning process?" Journal for New Generation Sciences, Vol 8, Issue 3: Central University of Technology, Free State, Bloemfontein, 2010. http://hdl.handle.net/11462/565.

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Published Article<br>The relationship between the big five personality traits, Extraversion, Agreeableness Neuroticism, Conscientiousness and Openness to Experience and deep and surface approaches to learning forms the basis of this article. The findings of a research study in this milieu will be presented to prove that earlier studies in this field have been upheld, but that an important deviation has occurred on certain levels of personality. A students way of learning implies the type of learning that is taking place. Ultimately we as lecturers want to encourage deep learning as this stimul

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Pon, Kumar Steven Spielberg. "Deep reinforcement learning approaches for process control." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/63810.

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The conventional and optimization based controllers have been used in process industries for more than two decades. The application of such controllers on complex systems could be computationally demanding and may require estimation of hidden states. They also require constant tuning, development of a mathematical model (first principle or empirical), design of control law which are tedious. Moreover, they are not adaptive in nature. On the other hand, in the recent years, there has been significant progress in the fields of computer vision and natural language processing that followed the suc

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Stamp, D. I. "Machine learning approaches to complex time series." Thesis, University of Liverpool, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.399317.

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It has been noted that there are numerous similarities between the behaviour of chaotic and stochastic systems. The theoretical links between chaotic and stochastic systems are investigated based on the evolution of the density of dynamics and an equivalency relationship based on the invariant measure of an ergodic system. It is shown that for simple chaotic systems an equivalent stochastic model can be analytically derived when the initial position in state space is only known to a limited precision. Based on this a new methodology for the modelling of complex nonlinear time series displaying

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Kwan, Sze-wai David, and 關思偉. "Thinking styles, learning approaches, and academic achievement." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31961666.

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Veropoulos, Konstantinos. "Machine learning approaches to medical decision making." Thesis, University of Bristol, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367661.

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23

Mbipom, Blessing. "Knowledge driven approaches to e-learning recommendation." Thesis, Robert Gordon University, 2018. http://hdl.handle.net/10059/3121.

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Learners often have difficulty finding and retrieving relevant learning materials to support their learning goals because of two main challenges. The vocabulary learners use to describe their goals is different from that used by domain experts in teaching materials. This challenge causes a semantic gap. Learners lack sufficient knowledge about the domain they are trying to learn about, so are unable to assemble effective keywords that identify what they wish to learn. This problem presents an intent gap. The work presented in this thesis focuses on addressing the semantic and intent gaps that

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McClellan, Timothy. "Creative learning approaches for undergraduate self-development." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/368989/.

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This thesis investigates creativity in the undergraduate curriculum and how students respond to creative approaches to learning within their studies. Specifically, the thesis considers how the use of multiple creative learning methods may enhance undergraduate learning and the role that creative visualisation and guided imagery can play in this experience. The thesis presents the learning stories of six undergraduates in the main study who took one of these modules. Interviews were conducted and a range of other documentary data, such as learning journals and assignments, was collected and ana

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Dang, Ha Xuan. "Mold Allergomics: Comparative and Machine Learning Approaches." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/64205.

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Fungi are one of the major organisms that cause allergic disease in human. A number of proteins from fungi have been found to be allergenic or possess immunostimulatory properties. Identifying and characterizing allergens from fungal genomes will help facilitate our understanding of the mechanism underlying host-pathogen interactions in allergic diseases. Currently, there is a lack of tools that allow us to rapidly and accurately predict allergens from whole genomes. In the context of whole genome annotation, allergens are rare compared to non-allergens and thus the data is considered highly s

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Sathyan, Anoop. "Intelligent Machine Learning Approaches for Aerospace Applications." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1491558309625214.

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27

Tortajada, Velert Salvador. "Incremental Learning approaches to Biomedical decision problems." Doctoral thesis, Universitat Politècnica de València, 2012. http://hdl.handle.net/10251/17195.

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During the last decade, a new trend in medicine is transforming the nature of healthcare from reactive to proactive. This new paradigm is changing into a personalized medicine where the prevention, diagnosis, and treatment of disease is focused on individual patients. This paradigm is known as P4 medicine. Among other key benefits, P4 medicine aspires to detect diseases at an early stage and introduce diagnosis to stratify patients and diseases to select the optimal therapy based on individual observations and taking into account the patient outcomes to empower the physician, the patient, and

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Wang, Yiqing. "Two Bayesian learning approaches to image processing." Thesis, Cachan, Ecole normale supérieure, 2015. http://www.theses.fr/2015DENS0007/document.

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Cette thèse porte sur deux méthodes à patch en traitement d’images dans le cadre de minimisation du risque Bayésien. Nous décrivons un mélange d’analyses factorielles pour modéliser la loi à priori des patchs dans une seule image et l’appliquons au débruitage et à l’inpainting. Nous étudions aussi les réseaux de neurones à multi-couches d’un point de vue probabiliste comme un outil permettant d’approcher l’espérance conditionnelle, ce qui ouvre quelques voies pour réduire leurs tailles et coût d’apprentissage<br>This work looks at two patch based image processing methods in a Bayesian risk min

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Xu, Sangni. "Deep Learning Approaches for Robust Monocular SLAM." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29714.

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Simultaneously Localisation and Mapping (SLAM) aims to determine the position of the camera and the map of an environment. It has been wildly used in various applications such as AR/VR, robotics, and autonomous driving. Since conventional methods largely rely on low-level hand-crafted features that are not robust, our research presented in this thesis utilises deep neural networks that directly learn to map the input of an image sequence to camera poses and/or depth maps. Previous works utilise convolutional neural network (CNN) to extract spatial features. To extract the temporal features

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Taheri, Sona. "Learning Bayesian networks based on optimization approaches." Thesis, University of Ballarat, 2012. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/36051.

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Learning accurate classifiers from preclassified data is a very active research topic in machine learning and artifcial intelligence. There are numerous classifier paradigms, among which Bayesian Networks are very effective and well known in domains with uncertainty. Bayesian Networks are widely used representation frameworks for reasoning with probabilistic information. These models use graphs to capture dependence and independence relationships between feature variables, allowing a concise representation of the knowledge as well as efficient graph based query processing algorithms. This repr

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Tuli, Sabrina Hoque. "Small Face Detection with Deep Learning Approaches." Thesis, Curtin University, 2021. http://hdl.handle.net/20.500.11937/86208.

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This thesis considers small face detection in uncontrolled environments and develops robust deep learning approaches for this challenging problem. A novel multi-scale face detector is developed by integrating novel anchor design, efficient regression loss and additional detection layers. Several multi-scale dense convolutional networks are developed to boost up the detection of small faces. Experimental results on public face databases demonstrate that the proposed methods outperform the state-of-the-art methods (e.g. YOLOv3) for detection of small faces.

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Amuru, SaiDhiraj. "Intelligent Approaches for Communication Denial." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/56695.

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Spectrum supremacy is a vital part of security in the modern era. In the past 50 years, a great deal of work has been devoted to designing defenses against attacks from malicious nodes (e.g., anti-jamming), while significantly less work has been devoted to the equally important task of designing effective strategies for denying communication between enemy nodes/radios within an area (e.g., jamming). Such denial techniques are especially useful in military applications and intrusion detection systems where untrusted communication must be stopped. In this dissertation, we study these offensive a

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Strang, Alison Bridget. "A model of learning : an investigation of technicians' approaches to open learning." Thesis, University College London (University of London), 1990. http://discovery.ucl.ac.uk/10018494/.

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The work arose from an applied research project commissioned by the Manpower Services Commission. The aim of the project was to produce guidelines for effective learning in the Open Tech, based on a thoroughly researched understanding of open learning at technician level. A review of the literature led to the proposal that the research should examine technicians' experiences of learning from a phenomenological perspective, with particular attention to the intentions and meanings underlying their approaches. In response to this proposal, a metatheory was formulated to establish the assumptions

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Ollerenshaw, Alison. "Learning through multimedia : the roles of prior knowledge and approaches to learning." Thesis, The Author [Mt.Helen, Vic.] :, 1999. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/44369.

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The effects of text-supplementing illustrations have been generally well etablished (Mayer, Bove, Bryman, Mars & Tapangco, 1996). However, these effects are not universal, and are influenced by learner factors including student approaches to learning and prior knowldge (Ollerenshaw, Aidman & Kidd, 1997)....<br>Master of Applied Science (Psychology)

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Lai, Ling-yan Edith. "Effects of cooperative learning on student learning outcomes and approaches to learning in sixth form geography." Click to view the E-thesis via HKUTO, 1991. http://sunzi.lib.hku.hk/HKUTO/record/B38627292.

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36

Stanzione, Vincenzo Maria. "Developing a new approach for machine learning explainability combining local and global model-agnostic approaches." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amslaurea.unibo.it/25480/.

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The last couple of past decades have seen a new flourishing season for the Artificial Intelligence, in particular for Machine Learning (ML). This is reflected in the great number of fields that are employing ML solutions to overcome a broad spectrum of problems. However, most of the last employed ML models have a black-box behavior. This means that given a certain input, we are not able to understand why one of these models produced a certain output or made a certain decision. Most of the time, we are not interested in knowing what and how the model is thinking, but if we think of a mo

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Tweed, Roger Gordon. "Learning considered within a cultural context Confucian and Socratic approaches /." online access from Digital Dissertation Consortium access full-text, 2000. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?NQ56637.

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Khan, Umair. "Self-supervised deep learning approaches to speaker recognition." Doctoral thesis, Universitat Politècnica de Catalunya, 2021. http://hdl.handle.net/10803/671496.

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In speaker recognition, i-vectors have been the state-of-the-art unsupervised technique over the last few years, whereas x-vectors is becoming the state-of-the-art supervised technique, these days. Recent advances in Deep Learning (DL) approaches to speaker recognition have improved the performance but are constrained to the need of labels for the background data. In practice, labeled background data is not easily accessible, especially when large training data is required. In i-vector based speaker recognition, cosine and Probabilistic Linear Discriminant Analysis (PLDA) are the two basic sco

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Fasel, Ian Robert. "Learning real-time object detectors probabilistic generative approaches /." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2006. http://wwwlib.umi.com/cr/ucsd/fullcit?p3216357.

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Thesis (Ph. D.)--University of California, San Diego, 2006.<br>Title from first page of PDF file (viewed July 24, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 87-91).

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Gulcehre, Caglar. "Two Approaches For Collective Learning With Language Games." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613109/index.pdf.

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Recent studies in cognitive science indicate that language has an important social function. The structure and knowledge of language emerges from the processes of human communication together with the domain-general cognitive processes. Each individual of a community interacts socially with a limited number of peers. Nevertheless societies are characterized by their stunning global regularities. By dealing with the language as a complex adaptive system, we are able to analyze how languages change and evolve over time. Multi-agent computational simulations assist scientists from different disci

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Nori, Nozomi. "Machine Learning Approaches for Personalized Clinical Risk Modeling." 京都大学 (Kyoto University), 2017. http://hdl.handle.net/2433/225729.

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Zhang, Yue. "Discriminative learning approaches for statistical processing of Chinese." Thesis, University of Oxford, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.510405.

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Trifonova, Neda. "Machine-learning approaches for modelling fish population dynamics." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/13386.

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Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. Understanding the nature of functional relationships (such as prey-predator) between species is important for building predictive models. However, modelling the interactions with external stressors over time and space is also essential for ecosystem-based approaches to fisheries management. With the recent adoption of more explorative tools, like Bayesian networks, in predictive ecolog

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Muppala, Sireesha. "Multi-tier Internet service management| Statistical learning approaches." Thesis, University of Colorado at Colorado Springs, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3560749.

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<p> Modern Internet services are multi-tiered and are typically hosted in virtualized shared platforms. While facilitating flexible service deployment, multi-tier architecture introduces significant challenges for Quality of Service (QoS) provisioning in hosted Internet services. Complex inter-tier dependencies and dynamic bottleneck tier shift are challenges inherent to tiered architectures. Hard-to-predict and bursty session-based Internet workloads further magnify this complexity. Virtualization of shared platforms adds yet another layer of complication in managing the hosted multi-tier Int

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Li, Jerry Zheng. "Principled approaches to robust machine learning and beyond." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120382.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<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 PDF version of thesis.<br>Includes bibliographical references (pages 305-320).<br>As we apply machine learning to more and more important tasks, it becomes increasingly important that these algorithms are robust to systematic, or worse, malicious, noise. Despite considerable interest, no efficient algorithms we

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Kim, Hyun Soo M. Eng Massachusetts Institute of Technology. "Two new approaches for learning Hidden Markov Models." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61287.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 99-100).<br>Hidden Markov Models (HMMs) are ubiquitously used in applications such as speech recognition and gene prediction that involve inferring latent variables given observations. For the past few decades, the predominant technique used to infer these hidden variables has been the Baum-Welch algorithm. This thesis utilizes insights from two related fields. The first insight is from Angluin's

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Potapov, Danila. "Supervised Learning Approaches for Automatic Structuring of Videos." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAM023/document.

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L'Interprétation automatique de vidéos est un horizon qui demeure difficile a atteindre en utilisant les approches actuelles de vision par ordinateur. Une des principales difficultés est d'aller au-delà des descripteurs visuels actuels (de même que pour les autres modalités, audio, textuelle, etc) pour pouvoir mettre en oeuvre des algorithmes qui permettraient de reconnaitre automatiquement des sections de vidéos, potentiellement longues, dont le contenu appartient à une certaine catégorie définie de manière sémantique. Un exemple d'une telle section de vidéo serait une séquence ou une personn

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Yang, Guoli. "Learning in adaptive networks : analytical and computational approaches." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/20956.

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The dynamics on networks and the dynamics of networks are usually entangled with each other in many highly connected systems, where the former means the evolution of state and the latter means the adaptation of structure. In this thesis, we will study the coupled dynamics through analytical and computational approaches, where the adaptive networks are driven by learning of various complexities. Firstly, we investigate information diffusion on networks through an adaptive voter model, where two opinions are competing for the dominance. Two types of dynamics facilitate the agreement between neig

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SEGUY, Vivien Pierre François. "Measure Transport Approaches for Data Visualization and Learning." Kyoto University, 2018. http://hdl.handle.net/2433/233857.

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Лещенко, Ольга Іллівна, Ольга Ильинична Лещенко, and Olha Illivna Leshchenko. "Effective Training Approaches to Learning/Teaching Business English." Thesis, Sumy State University, 2017. http://essuir.sumdu.edu.ua/handle/123456789/67270.

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Abstract:

English language teaching has gone through a radical shift of emphasis in the last forty years, beginning with the communicative revolution in the mid-1970-s. The English language teachers are no longer all alone in their role as trainers as they are able to bring parts of the outside world to the classroom. Beyond the trainer’s “chalk and talk” and the trainees’ language and communication practice there is a range of materials in different media, which help the trainer to turn the Business English classroom into a varied learning/teaching environment. While printed text remains the mo

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