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 4 of 4 for “"Out-of-Distribution Generalization"”.
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Methods for Enhancing Robustness and Generalization in Machine Learning
… methods for improving subgroup robustness and out of distribution generalization of machine learning models. First we introduce a formulation of Group DRO with soft group assignment. This formulation can be applied to data with noisy or uncertain group labels, or when only a small subset of the …
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Towards Out-of-distribution Problem for Reinforcement Learning
… high-quality models require a large amount of data, parameters as well as computation power. This originates from the curse of dimensionality and poor out-of-distribution generalization of current probabilistic models. Current machine learning models requires data points to be independently …
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COMPOSITIONAL OBJECT-CENTRIC REPRESENTATIONS FOR ROBUST VISUAL PERCEPTION
… significant advancements, real-world deployment of modern vision models in critical applications remains limited by poor out-of-distribution generalization, failures under occlusion, reliance on large high-quality datasets, and limited interpretability. We posit that these limitations arise from …
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Interpretable Physics-informed Machine Learning Methods for Scientific Modeling and Data Analysis
With the recent advancement of modern machine learning methods, there are now many exciting opportunities to use machine learning in scientific research, including for modeling and data analysis. Machine learning has the potential to become an indispensable tool for scientific discovery, but it is …