DeepFedNAS: Efficient Hardware-Aware Architecture Adaptation for Heterogeneous IoT Federations via Pareto-Guided Supernet Training
cs.LG, cs.CV, cs.DC
Submitted: 2026-01-21
Updated: 2026-09-25
Code: https://github.com/bostankhan6/DeepFedNAS
Terminology
Sources
- Federated Learning for Mobile Keyboard Prediction
- Towards Non-I.I.D. and Invisible Data with FedNAS: Federated Deep Learning via Neural Architecture Search
- Once-for-All: Train One Network and Specialize it for Efficient Deployment
- Deep Residual Learning for Image Recognition
- Federated Learning: Strategies for Improving Communication Efficiency
- FedProto: Federated Prototype Learning across Heterogeneous Clients
- Neural Architecture Search with Reinforcement Learning
- Direct Federated Neural Architecture Search
- Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks