Conditional computation in neural networks: Principles and research trends
S Scardapane, A Baiocchi, A Devoto… - Intelligenza …, 2024 - journals.sagepub.com
This article summarizes principles and ideas from the emerging area of applying conditional
computation methods to the design of neural networks. In particular, we focus on neural …
computation methods to the design of neural networks. In particular, we focus on neural …
Multi-path Routing For Conditional Information Gain Trellis using Cross-Entropy Search and Reinforcement Learning
Convolutional neural networks have made significant strides in solving computer-vision
tasks at the expense of high computational demands. This complexity hinders efficient …
tasks at the expense of high computational demands. This complexity hinders efficient …
Adaptive Layer Selection for Efficient Vision Transformer Fine-Tuning
Recently, foundation models based on Vision Transformers (ViTs) have become widely
available. However, their fine-tuning process is highly resource-intensive, and it hinders …
available. However, their fine-tuning process is highly resource-intensive, and it hinders …
[PDF][PDF] Optimizing On-Device Model Adaptation with Minimal Latency for Real-Time Personalized Applications
K Mehta, M Gupta, A Nair, S Desai, P Singh, T Peng… - 2024 - researchgate.net
Real-time personalized applications require optimized on-device model adaptation to
deliver immediate responses. This paper introduces a hybrid architecture that effectively …
deliver immediate responses. This paper introduces a hybrid architecture that effectively …
[PDF][PDF] Adaptive Inference Strategies for Enhanced Lightweight YOLOv5 Deployment
N Davis, O Miller, L Smith, E Wilson, S Lopez, A Brown - researchgate.net
Deploying YOLOv5 models in resourceconstrained environments presents several
challenges, particularly in balancing performance and efficiency. In this work, we introduce …
challenges, particularly in balancing performance and efficiency. In this work, we introduce …