Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks.
Torsten HoeflerDan AlistarhTal Ben-NunNikoli DrydenAlexandra PestePublished in: J. Mach. Learn. Res. (2021)
Keyphrases
- deep learning
- efficient inference
- neural network
- structured prediction
- probabilistic inference
- conditional random fields
- unsupervised learning
- machine learning
- markov random field
- mental models
- exact inference
- approximate inference
- markov networks
- supervised learning
- graphical models
- high dimensional
- artificial neural networks
- feed forward
- weakly supervised
- hidden variables
- graph structure
- pattern recognition
- object recognition
- training samples
- bayesian networks
- neural nets
- learning algorithm
- information retrieval
- multilayer perceptron
- back propagation
- training examples
- probabilistic model