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 7 of 7 for “"sample-efficient learning"”.
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Sample-efficient learning with self-supervision
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms
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Mechanisms of Multi-Object Working Memory and Motion Prediction in the Primate Brain
Sample-efficient learning and flexible generalization are hallmarks of intelligent behavior. Both sample-efficient learning and flexible generalization rely on re-using a mental model of the world in new contexts. For many decades, researchers in cognitive science, neuroscience, and machine …
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COMPOSITIONAL OBJECT-CENTRIC REPRESENTATIONS FOR ROBUST VISUAL PERCEPTION
… occlusion reasoning, generalization, and sample-efficient learning. To address this gap, this thesis proposes a unified object-centric representation framework with three stages: discovery, representation, and application. The proposed models improve robustness, sample efficiency, …
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Partially Supervised Reinforcement Learning for GPS-Denied Navigation
… relevant semantics. In this work, we propose a learning framework for aerial navigation in the presence of changing dynamics and limited positional information. Specifically, we consider a drone navigation task where a drone at one time has access to GPS location information, which it has now …
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Structure-utilized, Adaptive, and Efficient ML-based Proportional-Fair Scheduling in MIMO Networks for Non-stationary Channels
… sub-optimal performance. More recently, machine learning (ML)-based approaches have demonstrated strong performance with low latency. However, ML-based methods typically assume stationary channel distributions, making them vulnerable to performance degradation under dynamic network conditions …
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Sample-efficient reinforcement learning
Reinforcement learning has been instrumental in the recent advances made by artificial intelligence agents in various domains. Most of these advances have been abetted by the availability of huge amounts of training data. But, in several practical applications such as those arising in wireless …
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Structured machine learning for dynamical systems in healthcare
… variables. Recently, the advances of Machine Learning (ML) start to popularise the data-driven approach to dynamical system modelling, which employs automated algorithms to extract or approximate the governing equations from training data with minimum human inputs. Unlike the expert-driven …