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 13 of 13 for “"data-efficient learning"”.
-
Data-Efficient Learning in Image Synthesis and Instance Segmentation
Modern deep learning methods have achieve remarkable performance on a variety of computer vision tasks, but 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 …
-
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
-
Data-efficient learning for manipulation, locomotion, and information gathering involving granular media and deformable objects
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms
-
Bayesian Learning for Data-Efficient Control
… to finance, to industrial processing, autonomous learning helps obviate a heavy reliance on experts for system identification and controller design. Often real world systems are nonlinear, stochastic, and expensive to operate (e.g. slow, energy intensive, prone to wear and tear). Ideally …
-
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
-
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
-
Learning to Plan by Learning Rules
… naturally fluent with rules: we can learn rules efficiently; we can follow rules; we can interpret rules and explain them to others; and we can rapidly adjust to modified rules such as a new recipe without needing to relearn everything from scratch. By contrast, deep reinforcement learning (DRL) …
-
Towards Data Efficiency and Controllable Representations for Deep Learning in Resource-Constrained Domains
… two fundamental challenges: label scarcity and data scarcity. Label scarcity stems from the high cost of expert annotation, the scarcity of domain experts, and the infeasibility of crowdsourcing, particularly in complex tasks requiring specialised knowledge. In parallel, data scarcity stems from …
-
Data-efficient Neural Appearance Manipulations
… time and expertise. Consequently, machine learning (ML)-based approaches have emerged as key to the success of faster and accurate manipulations. This dissertation explores the potential of data-efficient learning-based techniques for manipulating three core aspects of appearance: fine …
-
Physics-informed machine learning for smart decision-making in ultrasonic metal welding
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01
-
Generalizing Under Data Scarcity. Enhancing the representation capability from few samples.
The widespread adoption of deep learning in both research and industrial contexts has revealed a central limitation: many real-world applications lack large, diverse, and reliably labeled datasets. This challenge is particularly evident in domains where data acquisition is costly, error-prone, or …
-
Advances in Active Learning and Sequential Decision Making
Much of the recent success of machine learning methods was enabled by exploiting the wealth of labeled data produced in the past few years. However, for several important real-world applications such large-scale data collection is still infeasible. This includes areas such as robotics, healthcare, …
-
Machine-learning-based measurement, modeling, and control of spatial variability in advanced manufacturing
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01