#neural architecture search
5 papers · 1 filter
Filling the Pareto-Optimal Front for Affordance Segmentation on Embedded Devices Using RGB-D Cameras
Edoardo Ragusa, Giovanni Paolo Canuti, Simone Lugani +2
The paper proposes hardware‑aware neural architecture search and a fine‑tuning pipeline to integrate depth data into compact RGB‑D networks for affordance segmentation on embedded…
Surrogate assisted diversity estimation in neural ensemble search
Alexandr Udeneev, Petr Babkin, Oleg Bakhteev
The paper proposes a dual‑objective surrogate‑guided method for neural ensemble search that predicts both accuracy and diversity of candidate architectures, enabling efficient cons…
Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions
Truong Giang Vu, Li Yang, Richard W. Pazzi
The paper surveys how neural architecture search techniques are used to automatically design deep learning models for traffic prediction, reviewing gradient‑based, evolutionary, an…
Transformer-Guided Swarm Intelligence for Frugal Neural Architecture Search
Romain Amigon
The paper introduces a hybrid Neural Architecture Search method that combines a reinforcement‑learning‑trained Transformer controller with an Artificial Bee Colony algorithm to eff…
Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis
Anujaya Vijayakumar, Radu Timofte, Dmitry Ignatov
The paper proposes a MinHash‑based curriculum that gradually presents neural‑architecture code of increasing diversity to a large language model, fine‑tuning it with LoRA adapters…