Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 36 for “"Structured learning"”.
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Multi-output structured learning
Real-world applications of Machine Learning (ML) require modeling and reasoning about complex, heterogeneous and high-dimensional data. Probabilistic Inference and Structured-Output Prediction (SOP) are frameworks within ML, which enable systems to learn and reason about complex output spaces by …
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Beyond multi-class – structured learning for machine translation
In this thesis, we explore and present machine learning (ML) approaches to a particularly challenging research area – machine translation (MT). The study aims at replacing or developing each component in the MT system with an appropriate discriminative model, where the ultimate goal is to create a …
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Efficient object detection via structured learning and local classifiers
… generation, we formulate this problem as a structured learning problem and investigate structural support vector machines (SSVMs) with our proposed scale/aspect-ratio quantization scheme and ranking constraints. A general ranking-order decomposition algorithm is developed for solving the …
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Selective algorithms for large-scale classification and structured learning
Made available in DSpace on 2015-07-22T22:17:14Z (GMT). No. of bitstreams: 2 CHANG-DISSERTATION-2015.pdf: 1718796 bytes, checksum: acb2f0fcac6237b94e5733d5534763cb (MD5) LICENSE.txt: 4210 bytes, checksum: 781f641005bc15b659d6f1cee238b5c2 (MD5) Previous issue date: 2015-04-23
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Online Structured Learning for Real-Time Computer Vision Gaming Applications
… research in this area we incorporate online learning to provide an appearance model which is able to adapt to the target object and its surrounding background during tracking. However, our approach moves beyond the standard framework of tracking using binary classication and instead …
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Structured learning and inference with neural networks and generative models
… fully satisfying as process models of human learning. This thesis aims to address this state of affairs from both directions, exploring case studies where we make neural networks that learn from less data, and in which we design more efficient inference procedures for generative models. …
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Structured Learning with Inexact Search: Advances in Shift-Reduce CCG Parsing
… parsing involves the interplay of representation learning, structured learning, and inexact search. This dissertation considers approaches that tightly integrate these three elements and explores three novel models for shift-reduce CCG parsing. First, I develop a dependency model, in which the …
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DATA-DRIVEN ANALYTICAL MODELS FOR IDENTIFICATION AND PREDICTION OF OPPORTUNITIES AND THREATS
… The proposed models and results provide structured output to inform the executive decision-making process concerning large engineering projects (LEPs). This research proposes new techniques that not only provide reliable timeseries predictions but uncertainty quantification to help make …
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ProgPlay: The Gamification Learning Platform
ProgPlay is a gamified web-based learning platform designed to make programming education engaging and accessible for beginners through interactive quizzes, experience points (XP), and competitive leader boards. The platform addresses common challenges faced by beginner programmers, such as …
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Learning based programming
Machine learning (ML) is the study of representations and algorithms used for building functions that improve their behavior with experience. Today, researchers in many domains are applying ML to solve their problems when conventional programming techniques have proven insufficient. The first such …
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The semantics of role labeling
… these relations are annotated. From the machine learning perspective, learning to predicting these relations is a structured learning problem. However, we only have the small (for commas) or partially annotated (for prepositions) datasets. To predict the new relations, we show that using …
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Unsupervised learning of disentangled representations for speech with neural variational inference models
Despite recent successes in machine learning, artificial intelligence is still far from matching human intelligence in many ways. Two important aspects are transferability and amount of supervision required. Take speech recognition for example: while humans can easily adapt to a new accent without …
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Equity and what secondary science teachers bring to the classroom
… strategies designed to promote content learning through culturally relevant curriculum. Instead, they use mainstream-situated approaches that develop science content knowledge, vocabulary, procedures, and skills targeted toward high achievement on state and district standardized tests …
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Evaluating the effectiveness of clinical practice benchmarking in improving the quality of care
… improvement benchmarking approach that involves structured learning from others in order to improve, accepting the subjective nature of health care. Evaluative research of clinical practice benchmarking requires mixed methods, quantitative and qualitative. This challenges the current reliance …
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Teaching Literacy with Simplified Instruction and Evidence-based Pedagogy to Improve Early Childhood Reading
… strategies they found effective, such as structured learning (I Do, We Do, You Do), student-centered teaching approaches emphasizing engagement and personalized learning, play-based learning as a core strategy, and social learning through peer cooperation. The mixed-method analysis …
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Object localization in natural images
"Object localization algorithms aim at finding out what objects exist in an image and where each object is. Object localization is fundamental to many computer vision problems. Simply knowing what is in the image is not enough when we want to reason about object properties such as shape, color or …
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Impact of the Self-Assessment Tool for Fieldwork Educator Competency on Selfperceived Competence of Occupational Therapy Fieldwork Educators
… a development plan to facilitate reflective learning. At the end of the student rotation fieldwork, educators retook the SAT-FWC to determine if the SAT-FWC affected their competency behaviors. The fieldwork educators were surveyed to understand their experiences with bringing the SAT-FWC and …
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Impact of learner control on learning in adaptable and personalised e-learning environments
… of learners‟ measure of control over their learning, while working in different online learning environments, and how this, in combination with a structured learning material selection according to their learning preferences, can affect their learning performance. A qualitative study was …
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Educational Interventions for Children with Autism Spectrum Disorders: Perceptions of Parents and Teachers in a Northeast Tennessee School System.
… early intervention using multiple methods; a structured learning environment; adult-mediated and peer-mediated interventions for social and communication skills; inclusion with a balance of direct services; support staff to facilitate inclusion; a functional approach to problem behaviors; …
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Retaining New Graduate Nurses: Creating A Model Inpatient Transition To Practice Program In A Large Healthcare System
… DEU model offers a novel approach by creating a structured learning environment with trained preceptors to support NGNs' professional growth and development. Methods: The implementation of the DEU involved developing a dedicated medical-surgical unit equipped with trained nurse preceptors and …
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