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Few-shot learning for new environment adaptation
Few-shot learning (FSL) allows effective adaptation to a new environment with limited
labeled data. In wireless communications, where environments may vary significantly, FSL …
labeled data. In wireless communications, where environments may vary significantly, FSL …
Information Bottleneck-Based Domain Adaptation for Hybrid Deep Learning in Scalable Network Slicing
Network slicing enables operators to efficiently support diverse applications on a shared
infrastructure. However, the evolving complexity of networks, compounded by inter-cell …
infrastructure. However, the evolving complexity of networks, compounded by inter-cell …
Transfer: Cross Modality Knowledge Transfer using Adversarial Networks--A Study on Gesture Recognition
Knowledge transfer across sensing technology is a novel concept that has been recently
explored in many application domains, including gesture-based human computer …
explored in many application domains, including gesture-based human computer …
Scaling Up Task Execution on Resource-Constrained Systems
Y Luo - 2023 - search.proquest.com
The ubiquity of executing machine learning tasks on embedded systems with constrained
resources has made efficient execution of neural networks on these systems under the CPU …
resources has made efficient execution of neural networks on these systems under the CPU …
UseClean: learning from complex noisy labels in named entity recognition
We investigate and refine denoising methods for NER task on data that potentially contains
extremely noisy labels from multi-sources. In this paper, we first summarized all possible …
extremely noisy labels from multi-sources. In this paper, we first summarized all possible …
Few-Shot Adaptive Learning for Robust Task-Oriented Semantic Communication
Task-oriented semantic communication (ToSC) emerges as a promising approach for
executing remote inference tasks. While existing ToSC systems are generally trained under …
executing remote inference tasks. While existing ToSC systems are generally trained under …
Network Slicing with Reinforcement Learning and Transfer Learning
T Hu - 2024 - mediatum.ub.tum.de
Network slicing, a pivotal aspect of 5G and beyond, allows operators to configure virtual
network instances tailored to diverse services with specific requirements. However …
network instances tailored to diverse services with specific requirements. However …