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 “"Task Transfer"”.
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MeMo: Meaningful, Modular Controllers via Noise Injection
… on simple to complex robot morphology transfer. We also show that the modules help in task transfer. On both structure and task transfer, MeMo achieves improved training efficiency to graph neural network and Transformer baselines.
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Task Localization, Similarity, and Transfer; Towards a Reinforcement Learning Task Library System
<p>This thesis develops methods of task localization, task similarity discovery, and task transfer for eventual use in a reinforcement learning task library system, which can effectively “learn to learn,” improving its performance as it encounters various tasks over the lifetime of the learning …
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Foundation Models for Protein Phenotype Prediction
… proteinand-phenotype inputs, achieve zero-shot task transfer, and generate free-form text phenotypes interleaved with retrieved protein sequence, structure, and drug modalities in a single unified model.
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Learning probabilistic relational dynamics for multiple tasks
… which little data exists for the desired target task. Transfer learning attempts to extract trends from the data of similar source tasks to enhance learning in the target task. We apply transfer learning to probabilistic rule learning to learn the dynamics of a target world. We utilize a …
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Transfer Learning For Spoken Language Processing
This thesis develops transfer learning paradigms for spoken language processing applications. In particular, we tackle domain adaptation in the context of Automatic Speech Recognition (ASR) and Cross-Lingual Learning in Automatic Speech Translation (AST). The first part of the thesis develops an …
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Training And Transfer Of Attentional Control In Older Adulthood
… and if so, how widely does that trained skill transfer? Previous research has demonstrated that older adults are able to improve their performance on laboratory cognitive tests and in some cases these benefits can transfer to other similar tests: e.g. Kramer et al., 2004). A few cases have …
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From thoughts to actions: cracking the neural code across scales and modalities
… enables cross-session, cross-subject, and cross-task transfer. This framework combines the versatility of transformers with the energy-benefits of spiking neural networks to enable robust, actionable decoding for closed-loop BCI systems that run on edge compute. Together, these works advance …