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Found 5 papers, 1 papers with code
Single-DARTS: Towards Stable Architecture Search
Differentiable architecture search (DARTS) marks a milestone in Neural Architecture Search (NAS), boasting simplicity and small search costs.
Neural Architecture Search with Random Labels
In this paper, we investigate a new variant of neural architecture search (NAS) paradigm -- searching with random labels (RLNAS).
Single-level Optimization For Differential Architecture Search
The bias causes the architecture parameters of non-learnable operations to surpass that of learnable operations.
VAENAS: Sampling Matters in Neural Architecture Search
In this paper, we propose a learnable sampling module based on variational auto-encoder (VAE) for neural architecture search (NAS), named as VAENAS, which can be easily embedded into existing weight sharing NAS framework, e. g., one-shot approach and gradient-based approach, and significantly improve the performance of searching results.
Elements of Effective Deep Reinforcement Learning towards Tactical Driving Decision Making
Tactical driving decision making is crucial for autonomous driving systems and has attracted considerable interest in recent years.
