Model pruning is arguably one of the oldest methods of deep neural networks (DNN) model size reduction that dates to the 90s, and quite stunningly, is still a very active area of research in the AI community. Pruning in a nutshell, creates sparsely connected DNNs that intend to retain model performance as the original dense model.
-
Articles récents
- Smart Waste Management: WasteAnt’s AI Solutions for Energy Generation
- Loop Replacement Strategies: Applications to Pandas Apply
- Clustering Time Series with PCA and DBSCAN
- Deploy Enterprise-Ready AI with Dell PowerEdge and Intel® Gaudi® 3
- Roofline AI’s Role in Advancing Compiler Technology with oneAPI
-
Neural networks news
Intel NN News
- Smart Waste Management: WasteAnt's AI Solutions for Energy Generation
“What if waste wasn’t just waste, but energy waiting to be unleashed?” Discover how […]
- Loop Replacement Strategies: Applications to Pandas Apply
This article shows how to apply the NumPy select tricks to accelerate the Pandas Apply statement […]
- Clustering Time Series with PCA and DBSCAN
This article shows how to perform clustering of time series data using PCA and DBSCAN.
- Smart Waste Management: WasteAnt's AI Solutions for Energy Generation