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 179 for “"Learning problems"”.
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Solving Machine Learning Problems
Can a machine learn Machine Learning? This work trains a machine learning model to solve machine learning problems from a University undergraduate level course. We generate a new training set of questions and answers consisting of course exercises, homework, and quiz questions from MIT’s 6.036 …
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Computation Approaches for Continuous Reinforcement Learning Problems
… 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 …
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Inducing succinct rules in machine learning problems
Machine Learning techniques, in particular induction algorithms, have been applied to the field of expert systems development in an effort to overcome the knowledge acquisition bottleneck. Many different induction algorithms have been developed. These utilise a number of different knowledge …
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Certifying robustness in inference and learning problems
… for inference, prediction, and decision-making problems when the underlying distributions governing the data are known and well-modeled. The research from the past few decades has provided powerful learning algorithms when such distributions cannot be easily modeled, for instance with high …
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Beneficial Initializations in Over-Parameterized Machine Learning Problems
… empirically analyze the phenomenon of transfer learning in overparameterized machine learning. We start by showing that in over-parameterized linear regression, transfer learning is equivalent to solving regression from a non-zero initialization. We use this finding to propose LLBoost, a …
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A Unified Robust Minimax Framework for Regularized Learning Problems
… to apply minimax related concepts to real-world learning tasks, we develop a new fault-tolerant classification framework to combat class noise for general multi-class classification problems; further, by studying the relationship between the majorizable function class and the minimax framework, …
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Metacognitive strategies and academic perfomance among children with learning problems
… and academic performance among children with learning problems. The metacognitive strategy instruction was based on a metalearning model. Thirty nine pupils with learning problems from grades 4 and 5 participated in the study. Academic performance data on curriculum based history tests and …
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Cognitive and emotional mathematics learning problems in primary and secondary school students
… between developmental dyscalculia, a specific learning difficulty of mathematics, and mathematics anxiety, a negative emotional reaction to mathematics tasks. The link between these maths learning issues was examined by measuring their prevalence in large samples of English primary (N = 1004; …
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A Description and Analysis of Children with Learning Problems Referred to a Reading Teacher
… and to identify the factors present in their problems, (3) to describe the factors to make them more easily recognized, and (4) to find possible solutions for the problems found to be present most often.</p>
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A Distributed Q-learning Classifier System for task decomposition in real robot learning problems
A distributed reinforcement-learning system is designed and implemented on a mobile robot for the study of complex task decomposition in real robot learning environments. The Distributed Q-learning Classifier System (DQLCS) is evolved from the standard Learning Classifier System (LCS) proposed by …
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The association between learning problems and learners' profiles in private practices in the Limpopo Province
… of this study is to show the association between learning problems and demographic factors, to examine the assessment of learning problems and to describe the profiles of learners with learning problems. Knowledge regarding the above-mentioned could be of assistance in paving the way to examine …
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Synthetic Data Generation and Sampling for Online Training of DNN in Manufacturing Supervised Learning Problems
… proven to be remarkably effective in supervised learning in critical manufacturing applications, such as AI-enabled automatic inspection, quality modeling, etc. However, there is a lack of performance guarantee of DNN models primarily due to data class imbalance, shifting distribution, …
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The Effectiveness of Conversational Skill Training on The Development of Communicative Competence in Children With Language and Learning Problems
… boys. These boys were identified as language and learning handicapped and were receiving both regular and special education instruction concurrent with speech and language therapy.
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The Effects of Instruction and Strategy Implementation on Increasing Mathematics Computation Skills for Students with Learning Problems: A Meta-Analysis
… and researchers that students with a Specific Learning Disability (SLD) often do not make adequate progress when using traditional instructional methods (Whinnery & Stecker, 1992). Therefore, teachers must experiment with different techniques in order to help these students succeed. Many …
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Investigation of the Prevalence of Learning Disabilities Within the Home-School Population of Southwest Michigan
… Michigan to investigate the incidence of learning disabilities (LD) within this group. At the same time, it is possible to investigate some of the criticisms of the learning disability field of study.</p> <p><em>Method</em>. Two hundred ninety-eight home-school children in southwest …
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The Learning Profile, a Screening Instrument for Adults: Development and Validity Studies (Employment, Industrial Training, Adult Education, Vocational)
In adult learning settings, such as adult basic education, vocational training, community colleges, prisons, and industrial training, certain students and trainees may exhibit evidence of learning problems. At present there is no measuring instrument to screen effectively for adult learning …
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Time Series Learning With Probabilistic Network Composites
… over time through integrated, multi-strategy learning. Its focus is on decomposable, concept learning problems for classification of spatiotemporal sequences. Systematic methods of task decomposition using attribute- driven methods, especially attribute partitioning, are investigated. This …
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