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.
Results
Showing 1 to 19 of 19 for “"Early Stopping"”.
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Early Stopping of a Neural Network via the Receiver Operating Curve.
… data, it appears effective to stop training as early as possible once getting AUC sufficiently large via integrating ROC/AUC analysis into the training process. In order to reduce learning costs involving the imbalanced data set of the uneven class distribution, random sampling and …
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An investigation of heterogeneous commuting mode choices through an Early Stopping Bayesian Data Assimilation approach
… the data samples. This dissertation develops an Early Stopping Bayesian Data Assimilation (ESBDA) estimator which enables an established behaviour model to be well adapted to a new context characterised by significantly lower data samples. We carry out the development using the Mixed-Logit as the …
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Curtailed phase II binary outcome trials and adaptive multi-outcome trials
… though, there is often no opportunity for early stopping when this occurs. Some existing designs do permit early stopping in this case, accordingly reducing the required sample size and potentially speeding up drug development. However, more improvements can be achieved by stopping early …
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Towards practical neural network meta-modeling
… and empirical variance estimates for practical early stopping of online optimization procedures. Our SRMs are state-of-the-art in performance prediction and early stopping.
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Methods for imbalanced data in sports analytics: improving injury prediction models
… model behavior, including regularization with early stopping to control overfitting, alternative outcome-generation schemes for synthetic data, decision-rule restructuring through constructed risk-score ensembles, and incremental increases in injury prevalence to study how discrimination …
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Learning to classify images without explicit human annotations
… network on the noisy candidate labels, and iii) early stop the training to avoid overfitting. With this procedure we exploit an intriguing property of overparameterized neural networks: While they are capable of perfectly fitting the noisy data, gradient descent fits clean labels faster than …
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Modified Kernel Principal Component Analysis and Autoencoder Approaches to Unsupervised Anomaly Detection
… of training errors to minimize the importance of early stopping and Percentile Loss (PL) training aims to prevent anomalous examples from contributing to parameter updates. Lastly, early stopping via Knee detection aims to limit the risk of over training. Ultimately, the two new modified proposed …
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Understanding and Estimating the Adaptability of Domain-Invariant Representations
… of our results include model selection, deciding early stopping, error detection, and predicting the adaptability of a model between domains.
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Statistical Gems in AI: Toward Reliable and Efficient Intelligence
… collaboration. Finally, we propose statistical early stopping rules that enhance generative efficiency while maintaining accuracy. Together, these studies uncover key “statistical gems” that bridge AI technology with trustworthy and efficient real-world deployment.
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Multi-objective evolutionary neural architecture search for recurrent neural networks
… methods such as weight inheritance, early stopping, and pruning of architectural unit connections during offspring generation, are investigated in the context of RNN architecture search to allow for more efficient exploration of the RNN architecture search space.
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Top-Down Synthesis for Library Learning
… it is robust to terminating the search procedure early—further allowing it to scale to challenging datasets by means of early stopping. We publish the code, the documentation, a tutorial, and a Python library for interfacing with our for our Rust implementation of Stitch. Tutorial & Documentation …
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Generated Image Quality Assurance and Generative Adversarial Network Augmentation for Machine Learning
… hyperparameter tuning of Pix2Pix, incorporating early stopping criteria to save time while maintaining high image quality. In addition, results are presented to validate the use of neural networks to predict the performance impact of different hyperparameter configurations, reducing the need for …
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Evaluating Temporal Queries over Videos
… and Temporal Matching (TM) separately with an early-stopping mechanism. We present the details of the above three research problems and our proposed methods. Via experiments conducted on various datasets, we show the effectiveness of our proposed methods.
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Bayesian Adaptive Designs for Early Phase Clinical Trials
… a response-adaptive randomization scheme with early stopping rules for futility and superiority. Bayesian posterior probabilities are used to make these decisions. Simulation studies demonstrate that the proposed design outperforms two conventional designs across a range of practical …
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Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks
… practices---namely, stochastic optimisation, early stopping and normalisation layers---when used for hyperparameter learning. We resolve these and construct a sample-based EM algorithm for scalable hyperparameter learning with linearised neural networks. We apply the above methods to perform …
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Advances in Variational Bayes Theory: Adaptation, Uncertainty Quantification, and Amortization
… Chapter 2 of this thesis proposes an early-stopping mechanism for variational Bayes adaptation. This framework is further extended to variational empirical Bayes and to frequentist penalized estimators. At the same time, modern applications demand not only statistical validity but also …
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Domain Adaptation using Deep Adversarial Models
… functions and an intelligent regularization and early stopping approach. We validate the hypotheses made on a multitude of standard linguistic tasks as well as one of our own making. As a part of this effort we mined and contributed an authorship data set that has been accepted for use as a …
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Bayesian Adaptive Designs For Early Phase Clinical Trials
… missing late-onset responses to make an early stopping decision.</p> <p>Treating patients with novel biological agents is becoming a leading trend in oncology. Unlike cytotoxic agents, for which toxicity and efficacy monotonically increase with dose, biological agents may exhibit …
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Bayesian Designs For Early Phase Clinical Trials With Novel Target Agents
… mainly focus on Bayesian designs for early phase clinical trials with novel target agents. It includes three specific topics: (1) reviewing novel phase I clinical trial designs and comparing their operating characteristics; (2) Proposing a Bayesian optimal phase II clinical trial …