Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bajpai, Divya Jyoti"'
Recent advances in Deep Neural Networks (DNNs) have demonstrated outstanding performance across various domains. However, their large size is a challenge for deployment on resource-constrained devices such as mobile, edge, and IoT platforms. To overc
Externí odkaz:
http://arxiv.org/abs/2410.05338
Deep neural networks (DNNs) have made significant progress in recognizing visual elements and generating descriptive text in image-captioning tasks. However, their improved performance comes from increased computational burden and inference latency.
Externí odkaz:
http://arxiv.org/abs/2410.04433
Pre-trained Language Models (PLMs) exhibit good accuracy and generalization ability across various tasks using self-supervision, but their large size results in high inference latency. Early Exit (EE) strategies handle the issue by allowing the sampl
Externí odkaz:
http://arxiv.org/abs/2410.04424
Pre-trained Language Models (PLMs), like BERT, with self-supervision objectives exhibit remarkable performance and generalization across various tasks. However, they suffer in inference latency due to their large size. To address this issue, side bra
Externí odkaz:
http://arxiv.org/abs/2405.15039
The availability of large annotated data can be a critical bottleneck in training machine learning algorithms successfully, especially when applied to diverse domains. Weak supervision offers a promising alternative by accelerating the creation of la
Externí odkaz:
http://arxiv.org/abs/2402.15472
The recent advances in Deep Neural Networks (DNNs) stem from their exceptional performance across various domains. However, their inherent large size hinders deploying these networks on resource-constrained devices like edge, mobile, and IoT platform
Externí odkaz:
http://arxiv.org/abs/2401.10541