AutoGO: automated computation graph optimization for neural network evolution
Abstract Optimizing Deep Neural Networks (DNNs) to obtain high-quality models for efficient
real-world deployment has posed multi-faceted challenges to machine learning engineers …
real-world deployment has posed multi-faceted challenges to machine learning engineers …
Building Optimal Neural Architectures using Interpretable Knowledge
Abstract Neural Architecture Search is a costly practice. The fact that a search space can
span a vast number of design choices with each architecture evaluation taking nontrivial …
span a vast number of design choices with each architecture evaluation taking nontrivial …
[PDF][PDF] The Future Role of Artificial Intelligence (AI) Design's Integration into Architectural and Interior Design Education is to Improve Efficiency, Sustainability, and …
AF Almaz, EAE El-Agouz, MT Abdelfatah… - Sustainability, and …, 2024 - researchgate.net
The integration of artificial intelligence (AI) in architecture is transforming the design process,
making it faster, more efficient, and more sustainable. AI serves as a starting point for …
making it faster, more efficient, and more sustainable. AI serves as a starting point for …
Conformal Prediction based Confidence for Latency Estimation of DNN Accelerators: A Black-box Approach
M Wess, D Schnöll, D Dallinger, M Bittner… - IEEE Access, 2024 - ieeexplore.ieee.org
Today, there exists a large number of different embedded hardware platforms for
accelerating the inference of Deep Neural Networks (DNNs). To enable rapid application …
accelerating the inference of Deep Neural Networks (DNNs). To enable rapid application …
Set-Nas: Sample-Efficient Training For Neural Architecture Search With Strong Predictor And Stratified Sampling
Sample-efficient neural architecture search (NAS) techniques have advanced rapidly. Two
lines of methods, namely neural predictor and sequential search, have shown promising …
lines of methods, namely neural predictor and sequential search, have shown promising …
Improving Neural Networks with Generalizable Performance Predictors and Generative Code Language Models
A Mishra - 2023 - dash.harvard.edu
Neural Architecture Search (NAS) is a growing field with many evolving facets of research,
from evaluation strategies and search space criterion to architecture optimization strategies …
from evaluation strategies and search space criterion to architecture optimization strategies …