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Dissertations / Theses on the topic 'Instance'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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1

Foulds, James Richard. "Learning Instance Weights in Multi-Instance Learning." The University of Waikato, 2008. http://hdl.handle.net/10289/2460.

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Multi-instance (MI) learning is a variant of supervised machine learning, where each learning example contains a bag of instances instead of just a single feature vector. MI learning has applications in areas such as drug activity prediction, fruit disease management and image classification. This thesis investigates the case where each instance has a weight value determining the level of influence that it has on its bag's class label. This is a more general assumption than most existing approaches use, and thus is more widely applicable. The challenge is to accurately estimate these weights
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2

BRAUNER, DANIELA FRANCISCO. "INSTANCE-BASED SCHEMA MATCHING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=12573@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Um mediador é um componente de software que auxilia o acesso a fontes de dados. Com o advento da Web, a construção de mediadores impõe desafios importantes, tais como a capacidade de fornecer acesso integrado a fontes de dados independentes e dinâmicas e a habilidade de resolver a heterogeneidade semântica entre os esquemas destas fontes. Para lidar com esses desafios, o alinhamento de esquemas é uma questão fundamental. Nesta tese são propostas abordagens de alinhamento de esquemas de classificação (tesauros) e esquemas c
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Latham, Andrew C. "Multiple-Instance Feature Ranking." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1440642294.

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4

Hsu, Ikung. "Robust Multiple Instance Learning." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case158648636659484.

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Boulmier, Daniel. "Preuve et instance prud'homale." Orléans, 2000. http://www.theses.fr/2000ORLE0008.

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Les sources internationales, européennes ou nationales, édictant le principe d'un droit à l'accès a un tribunal et a un procès équitable, permettent-elles l'effectivité de l’égalité des parties devant le juge national ? Cette interrogation, soulevée dans le cadre du procès prud'homal, amène à une recherche dépassant la stricte analyse du déroulement du procès, recherche qui démontre la corrélation fondamentale entre la preuve et l'instance prud'homale. Le principe accusatoire de la procédure civile est affirmé en droit français, mais le juge dispose de quelques pouvoirs inquisitoires. En outre
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Wang, Xiaobo. "Collaboration Instance Manager of UbiCollab 2008 : Collaboration Instance Synchronization and Management in P2P network." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9714.

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<p>This report is for my research of Collaboration Instance Manager of UbiCollab project. UbiCollab want to be the platform for ubiquitous collaborative active. UbiCollab project aims to develop a distributed collaborative platform which makes people in distributed space ubiquitous collaborate with friends and colleagues. Collaboration instance manager (CIM) is a core component of the UbiCollab platform, which manage such collaborative activities. My research topics of CIM include in the P2P network development by using JXME, the data synchronization through this P2P network and how to manag
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Cheung, Pak-Ming. "Kernel-based multiple-instance learning /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?COMP%202006%20CHEUNGP.

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8

Varges, Sebastian. "Instance-based Natural Language Generation." Thesis, University of Edinburgh, 2003. http://hdl.handle.net/1842/27574.

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In recent years, ranking approaches to Natural Language Generation have become increasingly popular. They abandon the idea of generation as a deterministic decision-making process in favour of approaches that combine overgeneration with ranking at some stage in processing. In this thesis, we investigate the use of instance-based ranking methods for surface realization in Natural Language Generation. Our approach to instance-based Natural Language Generation employs two basic components: a rule system that generates a number of realization candidates from a meaning representation and an instanc
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9

Martin, Richard George. "Instance-based symbolic pattern association." Thesis, University of Ulster, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388880.

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10

Doran, Gary Brian Jr. "Multiple-Instance Learning from Distributions." Case Western Reserve University School of Graduate Studies / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=case1417736923.

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11

Vijayanathasamy, Srikanthan Swetha. "THE K-MULTIPLE INSTANCE REPRESENTATION." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1575638743851926.

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12

He, Fengxiang. "Instance-Dependent Positive-Unlabelled Learning." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/20115.

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An emerging topic in machine learning is how to learn classifiers from datasets containing only positive and unlabelled examples (PU learning). This problem has significant importance in both academia and industry. This thesis addresses the PU learning problem following a natural strategy that treats unlabelled data as negative. By this way, a PU dataset is transferred to a fully-labelled dataset but with label noise. This strategy has been employed by many existing works and is usually called the one-side noise model. Under the framework of the one-side noise model, this thesis proposes an
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13

Xu, Xin. "Statistical Learning in Multiple Instance Problems." The University of Waikato, 2003. http://hdl.handle.net/10289/2328.

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Multiple instance (MI) learning is a relatively new topic in machine learning. It is concerned with supervised learning but differs from normal supervised learning in two points: (1) it has multiple instances in an example (and there is only one instance in an example in standard supervised learning), and (2) only one class label is observable for all the instances in an example (whereas each instance has its own class label in normal supervised learning). In MI learning there is a common assumption regarding the relationship between the class label of an example and the ``unobservable'' cla
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14

Hsiao, Edward. "Addressing Ambiguity In Object Instance Detection." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/309.

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In this thesis, we study the topic of ambiguity when detecting object instances in scenes with severe clutter and occlusions. Our work focuses on the three key areas: (1) objects that have ambiguous features, (2) objects where discriminative point-based features cannot be reliably extracted, and (3) occlusions. Current approaches for object instance detection rely heavily on matching discriminative point-based features such as SIFT. While one-to-one correspondences between an image and an object can often be generated, these correspondences cannot be obtained when objects have ambiguous featur
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15

Smith, Michael Reed. "An empirical study of instance hardness /." Diss., CLICK HERE for online access, 2010. http://contentdm.lib.byu.edu/ETD/image/etd3239.pdf.

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Smith, Michael Reed. "An Empirical Study of Instance Hardness." BYU ScholarsArchive, 2009. https://scholarsarchive.byu.edu/etd/2012.

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Most widely accepted measures of performance for learning algorithms, such as accuracy and area under the ROC curve, provide information about behavior at the data set level. They say nothing about which instances are misclassified, whether two learning algorithms with the same classification accuracy on a data set misclassify the same instances, or whether there are instances misclassified by all learning algorithms. These questions about behavior at the instance level motivate our empirical analysis of instance hardness, a measure of expected classification accuracy for an instance. We analy
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17

Sun, Xiantang. "Domain independent generation from RDF instance date." Thesis, Available from the University of Aberdeen Library and Historic Collections Digital Resources, 2008. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?application=DIGITOOL-3&owner=resourcediscovery&custom_att_2=simple_viewer&pid=24972.

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18

Boujari, Tahereh. "Instance-based ontology alignment using decision trees." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-84918.

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Using ontologies is a key technology in the semantic web. The semantic web helps people to store their data on the web, build vocabularies, and has written rules for handling these data and also helps the search engines to distinguish between the information they want to access in web easier. In order to use multiple ontologies created by different experts we need matchers to find the similar concepts in them to use it to merge these ontologies. Text based searches use the string similarity functions to find the equivalent concepts inside ontologies using their names.This is the method that is
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19

Dong, Lin. "A Comparison of Multi-instance Learning Algorithms." The University of Waikato, 2006. http://hdl.handle.net/10289/2453.

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Motivated by various challenging real-world applications, such as drug activity prediction and image retrieval, multi-instance (MI) learning has attracted considerable interest in recent years. Compared with standard supervised learning, the MI learning task is more difficult as the label information of each training example is incomplete. Many MI algorithms have been proposed. Some of them are specifically designed for MI problems whereas others have been upgraded or adapted from standard single-instance learning algorithms. Most algorithms have been evaluated on only one or two benchmark d
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20

Wu, Shuning. "Optimal instance selection for improved decision tree." [Ames, Iowa : Iowa State University], 2007.

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21

Al, Balushi Ibrahim. "Instance optimality in infinite-dimensional compressed sensing." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=121443.

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This thesis provides a thorough literature review of the newly founded theory of compressed sensing (CS), developed by Cand`es and his collaborators. The majority of the documented developments remain in the treatment of perfectly sparse signals in the finite dimensional setting. This was extended to the treatment of nearly sparse (compressible) signals in infinite-dimensions by Adcock and Hansen. A novel approach in analyzing the performance of CS, in the finite-dimensional setting, was developed by Cohen, Dahmen and DeVore where they study the effectiveness of CS. This is carried by comparin
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22

Yamamoto, Masaaki. "Potential object analysis : an instance-based approach." Thesis, University of Warwick, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283513.

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23

Liu, Ke. "Scheduling algorithms for instance-intensive cloud workflows." Swinburne Research Bank, 2009. http://hdl.handle.net/1959.3/68752.

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Thesis (PhD) - Swinburne University of Technology, Faculty of Engineering and Industrial Sciences, Centre for Complex Software Systems and Services, 2009.<br>A thesis submitted to CS3 - Centre for Complex Software Systems and Services, Faculty of Engineering and Industrial Sciences, Swinburne University of Technology for the degree of Doctor of Philosophy, 2009. Typescript. "June 2009". Bibliography: p. 122-135.
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Maskat, Ruhaila. "Pay-as-you-go instance-level integration." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/payasyougo-instancelevel-integration(35871ad5-a3a8-4bf1-943d-55bcc75e3c0d).html.

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With the growing demand for information in various domains, sharing of information from heterogeneous data sources is now a necessity. Data integration approaches promise to combine data from these different sources and present to the user a single, unified view of these data. However, although these approaches offer high quality services for the managing and integrating of data, they come with a high cost. This is because a great amount of manual effort to form relationships across data sources is needed to set up the data integration system. A newer variant of data integration, known as data
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25

LeBaron, Dean M. "CVIC: Cluster Validation Using Instance-Based Confidences." BYU ScholarsArchive, 2015. https://scholarsarchive.byu.edu/etd/5736.

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As unlabeled data becomes increasingly available, the need for robust data mining techniques increases as well. Clustering is a common data mining tool which seeks to find related, independent patterns in data called clusters. The cluster validation problem addresses the question of how well a given clustering fits the data set. We present CVIC (cluster validation using instance-based confidences) which assigns confidence scores to each individual instance, as opposed to more traditional methods which focus on the clusters themselves. CVIC trains supervised learners to recreate the clustering,
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26

Pufahl, Luise, Andreas Meyer, and Mathias Weske. "Batch regions : process instance synchronization based on data." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2014/6908/.

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Business process automation improves organizations’ efficiency to perform work. In existing business process management systems, process instances run independently from each other. However, synchronizing instances carrying similar characteristics, i.e., sharing the same data, can reduce process execution costs. For example, if an online retailer receives two orders from one customer, there is a chance that they can be packed and shipped together to save shipment costs. In this paper, we use concepts from the database domain and introduce data views to business processes to identify instances
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27

Chakraborty, Chiranjit. "Instance compression of parametric problems and related hierarchies." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/8920.

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We define instance compressibility ([13, 17]) for parametric problems in the classes PH and PSPACE.We observe that the problem ƩiCIRCUITSAT of deciding satisfiability of a quantified Boolean circuit with i-1 alternations of quantifiers starting with an existential quantifier is complete for parametric problems in the class Ʃp/i with respect to w-reductions, and that analogously the problem QBCSAT (Quantified Boolean Circuit Satisfiability) is complete for parametric problems in PSPACE with respect to w-reductions. We show the following results about these problems: 1. If CIRCUITSAT is non-unif
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28

Gripton, Adam W. "Geometric margin domain description with instance-specific margins." Thesis, Heriot-Watt University, 2011. http://hdl.handle.net/10399/2424.

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Support vector domain description (SVDD) is a useful tool in data mining, used for analysing the within-class distribution of multi-class data and to ascertain membership of a class with known training distribution. An important property of the method is its inner-product based formulation, resulting in its applicability to reproductive kernel Hilbert spaces using the “kernel trick”. This practice relies on full knowledge of feature values in the training set, requiring data exhibiting incompleteness to be pre-processed via imputation, sometimes adding unnecessary or incorrect data into the cl
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29

Yang, Cheng 1974. "Image database retrieval with multiple-instance learning techniques." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/50505.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.<br>Includes bibliographical references (p. 81-82).<br>In this thesis, we develop and test an approach to retrieving images from an image database based on content similarity. First, each picture is divided into many overlapping regions. For each region, the sub-picture is filtered and converted into a feature vector. In this way, each picture is represented by a number of different feature vectors. The user selects positive and negative image examples to train the system. During th
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Bishop, Griffin R. "Unsupervised Semantic Segmentation through Cross-Instance Representation Similarity." Digital WPI, 2020. https://digitalcommons.wpi.edu/etd-theses/1371.

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Semantic segmentation methods using deep neural networks typically require huge volumes of annotated data to train properly. Due to the expense of collecting these pixel-level dataset annotations, the problem of semantic segmentation without ground-truth labels has been recently proposed. Many current approaches to unsupervised semantic segmentation frame the problem as a pixel clustering task, and in particular focus heavily on color differences between image regions. In this paper, we explore a weakness to this approach: By focusing on color, these approaches do not adequately capture relati
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Wilkins, Nicolas Jon. "WHAT IS IN AN INSTANCE? PRACTICE CONTEXT EFFECTS." Kent State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=kent1373572972.

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32

Baader, Franz, Francesco Kriegel, and Adrian Nuradiansya. "Privacy-Preserving Ontology Publishing for EL Instance Stores." Springer, 2019. https://tud.qucosa.de/id/qucosa%3A70975.

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We make a first step towards adapting an existing approach for privacy-preserving publishing of linked data to Description Logic (DL) ontologies. We consider the case where both the knowledge about individuals and the privacy policies are expressed using concepts of the DL EL , which corresponds to the setting where the ontology is an EL instance store. We introduce the notions of compliance of a concept with a policy and of safety of a concept for a policy, and show how optimal compliant (safe) generalizations of a given EL concept can be computed. In addition, we investigate the complexity o
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Nguyen, Dat. "MULTIPLE-INSTANCE AND ONE-CLASS RULE-BASED ALGORITHMS." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3059.

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In this work we developed rule-based algorithms for multiple-instance learning and one-class learning problems, namely, the mi-DS and OneClass-DS algorithms. Multiple-Instance Learning (MIL) is a variation of classical supervised learning where there is a need to classify bags (collection) of instances instead of single instances. The bag is labeled positive if at least one of its instances is positive, otherwise it is negative. One-class learning problem is also known as outlier or novelty detection problem. One-class classifiers are trained on data describing only one class and are used in s
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Kaza, Siddharth. "Instance, Evolution, and Predictive Modeling of Social Networks." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/193625.

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Various phenomena within the information systems discipline can be studied using the social network paradigm that views social entities as nodes with links between them. The social network analysis (SNA) theory has applications in knowledge management, computer mediated communications, security informatics, and other domains. Challenges in SNA can be classified into three broad areas: instance modeling, evolution modeling, and predictive modeling. Instance modeling focuses on the study of static network properties, evolution modeling examines factors behind network growth, and predictive model
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Gujar, Sanket. "Pointwise and Instance Segmentation for 3D Point Cloud." Digital WPI, 2019. https://digitalcommons.wpi.edu/etd-theses/1290.

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The camera is the cheapest and computationally real-time option for detecting or segmenting the environment for an autonomous vehicle, but it does not provide the depth information and is undoubtedly not reliable during the night, bad weather, and tunnel flash outs. The risk of an accident gets higher for autonomous cars when driven by a camera in such situations. The industry has been relying on LiDAR for the past decade to solve this problem and focus on depth information of the environment, but LiDAR also has its shortcoming. The industry methods commonly use projections methods to create
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Grard, Matthieu. "Generic instance segmentation for object-oriented bin-picking." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEC015.

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Le dévracage robotisé est une tâche industrielle en forte croissance visant à automatiser le déchargement par unité d’une pile d’instances d'objet en vrac pour faciliter des traitements ultérieurs tels que la formation de kits ou l’assemblage de composants. Cependant, le modèle explicite des objets est souvent indisponible dans de nombreux secteurs industriels, notamment alimentaire et automobile, et les instances d'objet peuvent présenter des variations intra-classe, par exemple en raison de déformations élastiques.Les techniques d’estimation de pose, qui nécessitent un modèle explicite et su
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Morris, John Garrett. "Type Classes and Instance Chains: A Relational Approach." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/1010.

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Type classes, first proposed during the design of the Haskell programming language, extend standard type systems to support overloaded functions. Since their introduction, type classes have been used to address a range of problems, from typing ordering and arithmetic operators to describing heterogeneous lists and limited subtyping. However, while type class programming is useful for a variety of practical problems, its wider use is limited by the inexpressiveness and hidden complexity of current mechanisms. We propose two improvements to existing class systems. First, we introduce several nov
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Boltenhagen, Mathilde. "Process Instance Clustering Based on Conformance Checking Artefacts." Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG060.

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Les données d'événements devenant une source d'information omniprésente, les techniques d'analyse de données représentent une opportunité sans précédent pour étudier et réagir aux processus qui génèrent ces données. Le Process Mining est un domaine émergent qui comble le fossé entre les techniques d'analyse de données, comme le Data Mining, et les techniques de management des entreprises, à savoir, le Business Process Management. L'une des bases fondamentales du Process Mining est la découverte de modèles de processus formels tels que les réseaux de Petri ou les modèles BPMN qui tentent de don
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Dobslaw, Felix. "Automatic Instance-based Tailoring of Parameter Settings for Metaheuristics." Licentiate thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-14613.

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Many industrial problems in various fields, such as logistics, process management, orproduct design, can be formalized and expressed as optimization problems in order tomake them solvable by optimization algorithms. However, solvers that guarantee thefinding of optimal solutions (complete) can in practice be unacceptably slow. Thisis one of the reasons why approximative (incomplete) algorithms, producing near-optimal solutions under restrictions (most dominant time), are of vital importance. Those approximative algorithms go under the umbrella term metaheuristics, each of which is more or less
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Ragnesand, Simon. "Estimating Query Containment by querying a single database instance." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187257.

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This paper examines the possibility of simply querying a database as a fast approximation for the query containment problem and measures its accuracy compared with a proper solver. The algorithm for a Correct Query Containment solver, which is used for comparisons sake, as well as the approximative algorithm is laid out. The database that was used to approximate query containment is also discussed. The results are discussed as well as the areas that this method can be applied to. Further ways to increase the accuracy is discussed. The results show that while the method has some potential the a
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Park, Hae Won. "Robot learners: interactive instance-based learning with social robots." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53442.

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On one hand, academic and industrial researchers have been developing and deploying robots that are used as educational tutors, mediators, and motivational tools. On the other hand, an increasing amount of interest has been placed on non-expert users being able to program robots intuitively, which has led to promising research efforts in the fields of machine learning and human-robot interaction. This dissertation focuses on bridging the gap between the two subfields of robotics to provide personalized experience for the users during educational, entertainment, and therapeutic sessions with so
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Mosesson, Marcus. "Korean Bodybuilding : Cultural Hybrid or Instance of Cultural Homogenization?" Thesis, Stockholms universitet, Institutionen för Asien-, Mellanöstern- och Turkietstudier, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-157588.

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This study deals with the trend of male bodybuilding in Korea and investigates the motivations and aesthetic ideals of Korean male bodybuilders. The author of the study uses the few hitherto academic research works on the subject and tries to give an overview of the history of Korean bodybuilding. Besides, the author has conducted a digital survey in order to collect answers from Korean male bodybuilders about their motivations, aesthetic ideals, etc. The aesthetic ideals of the bodybuilders are then compared to the male aesthetic ideals of modern Korean society and also discussed in relation
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Kolhatkar, Dhanvin. "Real-Time Instance and Semantic Segmentation Using Deep Learning." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40616.

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In this thesis, we explore the use of Convolutional Neural Networks for semantic and instance segmentation, with a focus on studying the application of existing methods with cheaper neural networks. We modify a fast object detection architecture for the instance segmentation task, and study the concepts behind these modifications both in the simpler context of semantic segmentation and the more difficult context of instance segmentation. Various instance segmentation branch architectures are implemented in parallel with a box prediction branch, using its results to crop each instance's feature
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Montoya, Amanda Kay. "Conditional Process Analysis in Two-Instance Repeated-Measures Designs." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1530904232127584.

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Šťávová, Karolína. "Identifikace abnormálních EKG segmentů pomocí metody Multiple-Instance Learning." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442555.

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Heart arrhythmias are a very common heart disease whose incidence is rising. This thesis is focused on the detection of premature ventricular contractions from 12-lead ECG records by means of deep learning. The location of these arrhythmias (key instances) in the record was found using a technique based on Multiple-Instance Learning. In the theoretical part of the thesis, basic electrophysiology of the heart and deep learning with a focus on the convolutional neural networks are described. Afterward, a program was created using the Python programming language, which contains a model based on t
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Robb, Esther Anne. "Data-Efficient Learning in Image Synthesis and Instance Segmentation." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104676.

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Modern deep learning methods have achieve remarkable performance on a variety of computer vision tasks, but frequently require large, well-balanced training datasets to achieve high-quality results. Data-efficient performance is critical for downstream tasks such as automated driving or facial recognition. We propose two methods of data-efficient learning for the tasks of image synthesis and instance segmentation. We first propose a method of high-quality and diverse image generation from finetuning to only 5-100 images. Our method factors a pretrained model into a small but highly expressive
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Zhang, Chi. "Apply on Instance of IBM Watson Cognitive Computing System." Thesis, KTH, Industriell ekologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-203999.

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Smart Cities concern a variety of domains such as information, data, energy, transport, health, etc. The ‘Information Age’, which shifts from the Industrial Revolution to information computerisation, accesses to large volumes of data explored by sophisticated computer based analytics. ICT solutions interconnect businesses and customers through the cloud while driving the global economy and development of Smart Cities. This MSc thesis aims to investigate connections between Smart Cities and cloud-based Cognitive Computing, then demonstrate with instances how the combination of Watson cognitive
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48

Belkhir, Nacim. "Per Instance Algorithm Configuration for Continuous Black Box Optimization." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS455/document.

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Cette thèse porte sur la configurationAutomatisée des algorithmes qui vise à trouver le meilleur paramétrage à un problème donné ou une catégorie deproblèmes.Le problème de configuration de l'algorithme revient doncà un problème de métaFoptimisation dans l'espace desparamètres, dont le métaFobjectif est la mesure deperformance de l’algorithme donné avec une configuration de paramètres donnée.Des approches plus récentes reposent sur une description des problèmes et ont pour but d’apprendre la relationentre l’espace des caractéristiques des problèmes etl’espace des configurations de l’algorithme
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49

Venkataramanan, Shashanka. "Metric learning for instance and category-level visual representation." Electronic Thesis or Diss., Université de Rennes (2023-....), 2024. http://www.theses.fr/2024URENS022.

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Le principal objectif de la vision par ordinateur est de permettre aux machines d'extraire des informations significatives à partir de données visuelles, telles que des images et des vidéos, et de tirer parti de ces informations pour effectuer une large gamme de tâches. À cette fin, de nombreuses recherches se sont concentrées sur le développement de modèles d'apprentissage profond capables de coder des représentations visuelles complètes et robustes. Une stratégie importante dans ce contexte consiste à préentraîner des modèles sur des ensembles de données à grande échelle, tels qu'ImageNet, p
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Boulmier, Daniel. "Preuve et instance prud'homale : à la recherche d'un procès équitable /." Paris : LGDJ, 2002. http://www.gbv.de/dms/sbb-berlin/350665133.pdf.

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