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 64 for “"data-efficient"”.
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Data Efficient Reinforcement Learning
… However, many state-of-the-art algorithms are data-hungry and computationally expensive, requiring large amounts of data to succeed. While this is possible for certain scenarios, in applications arising in social sciences and healthcare for example, where available data is sparse, this …
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TOWARDS DATA-EFFICIENT DEEP LEARNING
This thesis advances data-efficient machine learning by tackling the limitations of current dataset distillation (DD) methods, which aim to compress large datasets into compact synthetic ones for faster training and enhanced privacy. First, it introduces Dataset Factorization, a novel framework …
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Data-efficient quickest change detection
… associated with taking observations or acquiring data. For such applications, the classical quickest change detection model is no longer applicable. In this dissertation we extend the classical formulations by adding an additional penalty on the cost of observations used before the change point. …
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Data-efficient Neural Appearance Manipulations
… This dissertation explores the potential of data-efficient learning-based techniques for manipulating three core aspects of appearance: fine details, transient attributes, and reflectance. It introduces two novel contributions: (1) an ML-based image map representation designed for fine detail …
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Bayesian Learning for Data-Efficient Control
… system interaction. This thesis considers data efficient autonomous learning of control of nonlinear, stochastic systems. Data efficient learning critically requires probabilistic modelling of dynamics. Traditional control approaches use deterministic models, which easily overfit data, …
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Data-Efficient Machine Learning for Computational Imaging
This thesis presents a method that improves data efficiency in computational imaging by incorporating prior knowledge from physical models into machine learning algorithms. Our approach optimizes image reconstruction from sparse and noisy datasets by utilizing physical constraints to guide deep …
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Data-efficient approaches for audio classification and separation
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms
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Data-Efficient Machine Learning with Applications to Cardiology
… is that they often need to be trained on large datasets in order to be most effective. In domains such as medicine, large datasets are not always available, and thus there is a need for data-efficient models that perform well even in limited data regimes. In this thesis, motivated by this need, …
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Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents
… significantly when subjected to severe data scarcity and the presence of heterogeneous agents. In this work, we propose a model-based offline RL method to approach this setting. Using all available data from the various agents, we construct personalized simulators for each individual …
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Data-Efficient Machine Learning with Focus on Transfer Learning
… 1) insufficient high-quality training data, 2) costly training process, and 3) domain discrepancy. Therefore, it is important to develop solutions for these problems, so the future of ML will be more sustainable. Recently, a new concept, data-efficient ma- chine learning (DEML), has …
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Self-supervised learning for data-efficient human activity recognition
… sensing, which involves obtaining and analysing data from mobile devices and the environment, has emerged as an active research area. It captures the unique opportunity for mobile devices to offer insight into user behaviours. Within mobile sensing, human activity recognition is a fundamental …
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Data-Efficient Bilingual Lexicon Induction with Pretrained Language Models
… (BLI) and proposes a series of innovative data-efficient BLI approaches aimed at automatically inducing high-quality bilingual dictionaries in low-data scenarios, thereby bridging the lexical gaps between languages. While previous BLI methods rely on mapping static word embeddings, inspired …
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Data-Efficient Learning in Image Synthesis and Instance Segmentation
… frequently require large, well-balanced training datasets to achieve high-quality results. Data-efficient performance is critical for downstream tasks such as automated driving or facial recognition. We propose two methods of data-efficient learning for the tasks of image synthesis and instance …
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Data-efficient machine learning for decision-making in smart manufacturing
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Data-efficient machine learning for decision-making in smart manufacturing
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Optical domain subsampling for data-efficient optical coherence tomography (OCT)
… A description of the laser, interferometer, data acquisition system, and signal processing steps is given, and the results of point spread functions compressed into a baseband window are presented. Images that were taken with the subsampled OCT system and a wide-field microscope show that …
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Data-Efficient Learning Frameworks for Adaptive Intelligent Robots in Human-Robot Collaboration Scenarios
L'abstract è presente nell'allegato / the abstract is in the attachment
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PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Latent Factor Representation
… learning, where a policy is learned from a fixed dataset of trajectories without further interaction with the environment, is one of the greatest challenges in reinforcement learning. Despite its compelling application to large, real-world datasets, existing RL benchmarks have struggled to perform …
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Code generation and runtime techniques for enabling data-efficient deep learning training on GPUs
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms
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Robust and Data-Efficient Metamodel-Based Approaches for Online Analysis of Time-Dependent Systems
… of a system based on a limited amount of data collected when experiments with real systems are costly or impractical. As a popular metamodeling method, Gaussian process regression (GPR), has been successfully applied to analyses of various engineering systems. However, GPR-based …
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