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 166 for “"pre-training"”.
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Synthetic pre-training for robustness in information retrieval
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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Predicting learning success from patterns of pre-training magnetic resonance images
… cognitive and psychomotor tasks improves with training, yet the extent of improvement varies among individuals. Is it possible to forecast the benefit that a person might reap from training? What is the mechanism underlying learning? Several behavioral measures have been used to predict …
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Beyond pre-training: continual learning and hallucinations in transformer-based language models.
Pre-trained transformer models have become the norm for various language modelling tasks from document similarity analysis and text classification to natural language generation. Despite the impressive performance on benchmark datasets, adopting pretrained models for real-world applications often …
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The Effects of Pre-Training and Fine-Tuning CLIP with Domain-Specific Data
… relevant items to the buyers, Mercari utilizes a pre-trained model called Contrastive Language-Image Pre-training (CLIP), famed for its exceptional zero-shot performances, to support the auto-filling feature for item listing and similar items recommendation. As this model is pre-trained on a …
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Training a massively multimodal transformer on YouTube data: pre-training and parameter efficient fine-tuning on HPC infrastructure
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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Can a pre-training biomechanical pathway identify the most effective exercise to enhance a given group’s, subgroup’s or individual’s countermovement jump height?
… the drop jump, squat, jump squat and power clean training exercises are each purported to enhance maximal CMJ jump height, there are generally inconsistent findings regarding their effectiveness at doing so. The resounding implication of this is that a coach cannot be sure as to which training …
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Using Computer Simulations as a Pre-Training Activity in a Hands-On Lab to Help Community College Students Improve Their Understanding of Physics
… effectiveness of using computer simulations as a pre-training activity to a hands-on lab to improve students’ understanding of induction topics in physics. The computer simulation activity was compared to an overview presentation. Conceptual understanding and spatial ability were measured. A …
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Employment and Welfare-to-Work Training Initiatives: The Effects of Pre-Training Attitudes on Job-Search Behavior, Employment Status, and Job-Search Intended Effort
… were administered to participants in three training agencies to examine individual pre-training attitudinal and behavioral variables, including self-efficacy, employment commitment, and unemployment negativity. The study then examined the relationship between these variables and …
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The Relative Effects of Pre Training Learners and Exemplar and Non Exemplar Video Skills Training on the Acquisition and Generalized Maintenance of Signing in Toddlers
Behavioral skills training (BST) packages have been demonstrated to be an effective method of training parents and family members to train skillful implementation of discrete trial teaching (DTT). Video modeling can be used as an effective means to teach a variety of skills with the BST packages. …
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Acquisition of the Oddity Concept by a Harris Hawk: Form versus Motion
<p>The present study was intended to be an investigation of simple oddity learning by a Harris hawk through the use of stimuli in two conditions: form and motion. The study was to have consisted of a pre-training phase, a training phase, and a testing phase. However, due to the fact that the …
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Deep learning of visual features with limited supervision.
… models require large-scale labeled data for training, but obtaining annotations is costly in fields like medical imaging and underwater imaging. This dissertation explores methods for learning deep visual features with limited human supervision, expanding deep learning’s applicability to …
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Leveraging Structure and Knowledge in Clinical and Biomedical Representation Learning
… the tasks. These problems motivate the use of representation learning in this domain, which encompasses a variety of techniques designed to produce representations of a dataset that are amenable to downstream modelling tasks. Representation learning in this domain can also take advantage of the …
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Theoretical Understanding of Neural Network Optimization Landscape and Self-Supervised Representation Learning
… is their ability to automatically learn useful representations from data. Self-supervised representation learning, which learns the representations during pre-training and applies learned representations in downstream tasks, has become the dominant approach for representation learning in recent …
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Structural Self-Supervised Objectives for Transformers
… unsupervised raw data to develop more efficient pre-training objectives and self-supervised tasks that align well with downstream applications. In the first part, we present three alternative objectives to BERT’s Masked Language Modeling (MLM), namely Random Token Substitution (RTS), …
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The effect of trunk stability and leg strength training on vertical take-off velocity in athletes
… was to determine the effect of trunk stability training on the performance of vertical jumping as assessed by vertical take-off velocity. Athletes (20 males, 35 females) were randomly assigned to one of four training groups: trunk stability (TS), leg strength (LS), trunk stability and leg …
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A Data-Based Perspective on Model Reliability
… have been mislabelled, corrupted, or underrepresented during training. In such settings, the set of features that a model relies on, or its feature prior, often determines the model’s ultimate reliability. While many factors contribute to a model’s feature prior, recent evidence indicates …
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