Automatic relation-aware graph network proliferation
Graph neural architecture search has sparked much attention as Graph Neural Networks
(GNNs) have shown powerful reasoning capability in many relational tasks. However, the …
(GNNs) have shown powerful reasoning capability in many relational tasks. However, the …
Gennape: Towards generalized neural architecture performance estimators
KG Mills, FX Han, J Zhang, F Chudak… - Proceedings of the …, 2023 - ojs.aaai.org
Predicting neural architecture performance is a challenging task and is crucial to neural
architecture design and search. Existing approaches either rely on neural performance …
architecture design and search. Existing approaches either rely on neural performance …
Dynamic ensemble of low-fidelity experts: Mitigating nas “cold-start”
Abstract Predictor-based Neural Architecture Search (NAS) employs an architecture
performance predictor to improve the sample efficiency. However, predictor-based NAS …
performance predictor to improve the sample efficiency. However, predictor-based NAS …
PredNAS: A Universal and Sample Efficient Neural Architecture Search Framework
In this paper, we present a general and effective framework for Neural Architecture Search
(NAS), named PredNAS. The motivation is that given a differentiable performance estimation …
(NAS), named PredNAS. The motivation is that given a differentiable performance estimation …
Latent Space Neural Architecture Search via LambdaNDCGloss-Based Listwise Ranker
The rapid development of neural architecture search (NAS) promotes the research of
efficient evaluation of candidate architectures. However, as one of highly efficient evaluation …
efficient evaluation of candidate architectures. However, as one of highly efficient evaluation …