Holistic network virtualization and pervasive network intelligence for 6G
In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …
One-shot model for mixed-precision quantization
Neural network quantization is a popular approach for model compression. Modern
hardware supports quantization in mixed-precision mode, which allows for greater …
hardware supports quantization in mixed-precision mode, which allows for greater …
AI-driven collaborative resource allocation for task execution in 6G-enabled massive IoT
In the foreseeable future, the rapid growth of devices in the Internet of Things (IoT) will make
it difficult for 5G networks to ensure sufficient network resources. 6G technology has …
it difficult for 5G networks to ensure sufficient network resources. 6G technology has …
Bitwidth-adaptive quantization-aware neural network training: A meta-learning approach
Deep neural network quantization with adaptive bitwidths has gained increasing attention
due to the ease of model deployment on various platforms with different resource budgets. In …
due to the ease of model deployment on various platforms with different resource budgets. In …
Accelerating general-purpose lossless compression via simple and scalable parameterization
The storage of multi-media data can benefit from the advancements in general-purpose
lossless compression. The explosive growth of multi-media data volume in data centers …
lossless compression. The explosive growth of multi-media data volume in data centers …
Improving natural language understanding with computation-efficient retrieval representation fusion
Retrieval-based augmentations that aim to incorporate knowledge from an external
database into language models have achieved great success in various knowledge …
database into language models have achieved great success in various knowledge …
Lightweight and accurate DNN-based anomaly detection at edge
Deep neural networks (DNNs) have been showing significant success in various anomaly
detection applications such as smart surveillance and industrial quality control. It is …
detection applications such as smart surveillance and industrial quality control. It is …
Holistic Network Virtualization and Pervasive Network Intelligence for 6G
In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …
Information-ordered bottlenecks for adaptive semantic compression
We present the information-ordered bottleneck (IOB), a neural layer designed to adaptively
compress data into latent variables ordered by likelihood maximization. Without retraining …
compress data into latent variables ordered by likelihood maximization. Without retraining …
Bayesian nested neural networks for uncertainty calibration and adaptive compression
Nested networks or slimmable networks are neural networks whose architectures can be
adjusted instantly during testing time, eg, based on computational constraints. Recent …
adjusted instantly during testing time, eg, based on computational constraints. Recent …