On accelerating iterative algorithms with CUDA: A case study on Conditional Random Fields training algorithm for biological sequence alignment.
Zhihui DuZhaoming YinWenjie LiuDavid A. BaderPublished in: BIBM Workshops (2010)
Keyphrases
- conditional random fields
- training algorithm
- iterative algorithms
- sequence alignment
- pairwise
- gpu accelerated
- back propagation
- neural network
- comparative genomics
- protein structure prediction
- sequence labeling
- learning algorithm
- support vector machine
- markov random field
- graphical models
- supervised training
- higher order
- probabilistic model
- information extraction
- hidden markov models
- protein sequences
- training process
- amino acids
- learning rate
- generative model
- dynamic programming
- binding sites
- artificial neural networks
- rbf neural network
- hidden layer
- image processing
- computer vision
- feed forward
- reinforcement learning
- data sets