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Bayesian asymmetric quantized neural networks
Jen Tzung Chien
*
, Su Ting Chang
*
Corresponding author for this work
Department of Electrical and Computer Engineering
Research output
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Contribution to journal
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Article
›
peer-review
7
Scopus citations
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Keyphrases
Quantized Neural Networks
100%
M-ary
71%
Neural Network
42%
Spike-and-slab Prior
28%
Multiple Spike
28%
Recognition Task
14%
Memory Models
14%
Two-directional
14%
Heterogeneous Data
14%
Image Recognition
14%
Memory Storage
14%
Memory Cost
14%
Neural Network Training
14%
Parameter Space
14%
Binary Weights
14%
Quantization Level
14%
Storage Capacity
14%
Training Model
14%
Parameter Adaptation
14%
Variational Inference
14%
Neural Representation
14%
Classification Network
14%
Model Compression
14%
Asymmetric Learning
14%
Parameter Quantization
14%
Model Capacity
14%
Evidence Lower Bound
14%
Asymmetric Partitioning
14%
Ternary Weights
14%
Engineering
Test Time
100%
Neural Network Training
100%
Image Recognition
100%
Parameter Space
100%
Quantization Level
100%
Classification Network
100%
Computer Science
Neural Network
100%
Heterogeneous Data
10%
Storage Capacity
10%
Parameter Space
10%
Neural Network Training
10%
Adaptive Parameter
10%
Model Compression
10%
Quantization Level
10%
Neural Representation
10%
Chemical Engineering
Neural Network
100%