A Zero-Shot NAS Method for SAR Ship Detection Under Polynomial Search Complexity
H Wei, Z Wang, G Hua, Y Ni - IEEE Signal Processing Letters, 2024 - ieeexplore.ieee.org
One-shot neural architecture search (NAS) has achieved impressive results in the field of
synthetic aperture radar (SAR) ship detection. However, it is a challenge to balance …
synthetic aperture radar (SAR) ship detection. However, it is a challenge to balance …
CAGAN: Constrained neural architecture search for GANs
Recently, a number of Neural Architecture Search (NAS) methods have been proposed to
automate the design of Generative Adversarial Networks (GANs). However, due to the …
automate the design of Generative Adversarial Networks (GANs). However, due to the …
Hypergraph Neural Architecture Search
W Lin, X Peng, Z Yu, T Jin - Proceedings of the AAAI Conference on …, 2024 - ojs.aaai.org
In recent years, Hypergraph Neural Networks (HGNNs) have achieved considerable
success by manually designing architectures, which are capable of extracting effective …
success by manually designing architectures, which are capable of extracting effective …
MA-Net: Rethinking Neural Unit in the Light of Astrocytes
The artificial neuron (NN) model-based networks have accomplished extraordinary success
for various vision tasks. However, as a simplification of the mammal neuron model, their …
for various vision tasks. However, as a simplification of the mammal neuron model, their …
Exploring Universal Intrinsic Task Subspace for Few-shot Learning via Prompt Tuning
Why can pre-trained language models (PLMs) learn universal representations and
effectively adapt to broad NLP tasks differing a lot superficially? In this work, we empirically …
effectively adapt to broad NLP tasks differing a lot superficially? In this work, we empirically …
Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for Large Language Models
Despite the remarkable capabilities, Large Language Models (LLMs) face deployment
challenges due to their extensive size. Pruning methods drop a subset of weights to …
challenges due to their extensive size. Pruning methods drop a subset of weights to …
Automated Dominative Subspace Mining for Efficient Neural Architecture Search
Neural Architecture Search (NAS) aims to automatically find effective architectures within a
predefined search space. However, the search space is often extremely large. As a result …
predefined search space. However, the search space is often extremely large. As a result …
CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework
This work presents a novel approach to neural architecture search (NAS) that aims to
increase carbon efficiency for the model design process. The proposed framework CE-NAS …
increase carbon efficiency for the model design process. The proposed framework CE-NAS …