Neural Architecture Search

A Dynamic Variational Framework for Open-World Node Classification in Structured Sequences
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Multi-Relational Graph Neural Architecture Search with Fine-grained Message Passing
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Unifying Graph Contrastive Learning with Flexible Contextual Scopes
Graph contrastive learning (GCL) has recently emerged as an effective learning paradigm to alleviate the reliance on labelling …
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iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
Differentiable ARchiTecture Search(DARTS) has recently become the mainstream in the neural architecture search (NAS) due to its …
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One-Shot Neural Architecture Search: Maximising Diversity to Overcome Catastrophic Forgetting
One-shot neural architecture search (NAS) has recently become mainstream in the NAS community because it significantly improves …
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Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement
Recent works on One-Shot Neural Architecture Search (NAS) mostly adopt a bilevel optimization scheme to alternatively optimize the …
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A Relation-Specific Attention Network for Joint Entity and Relation Extraction
Joint extraction of entities and relations is an important task in natural language processing (NLP), which aims to capture all …
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One-Shot Neural Architecture Search via Novelty Driven Sampling
One-Shot Neural architecture search (NAS) has received wide attention due to its computational efficiency. Many One-Shot NAS methods …
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Overcoming Multi-Model Forgetting in One-Shot NAS with Diversity Maximization
One-Shot Neural Architecture Search (NAS) significantly improves the computational efficiency through weight sharing. However, this …
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