Contribution-Aware Bandwidth Allocation for Multimodal Split Learning
cs.LG, cs.DC, cs.NI
Submitted: 2026-09-01
Updated: 2026-09-01
Terminology
Sources
- Split learning for health: Distributed deep learning without sharing raw patient data
- A Federated Learning Framework for Healthcare IoT devices
- Contribution-Guided Asymmetric Learning for Robust Multimodal Fusion under Imbalance and Noise
- AutoEncoder-Compressed Parallel Split Learning for Pre-trained Model Fine-Tuning
- SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities
- Distributed LLMs and Multimodal Large Language Models: A Survey on Advances, Challenges, and Future Directions
- Improving neural networks by preventing co-adaptation of feature detectors
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