Variational Boosting: Iteratively Refining Posterior Approximations.
Andrew C. MillerNicholas J. FotiRyan P. AdamsPublished in: ICML (2017)
Keyphrases
- variational methods
- free energy
- posterior distribution
- image segmentation
- probability distribution
- bayesian framework
- probabilistic model
- ensemble learning
- ensemble methods
- weak hypotheses
- weak learners
- feature selection
- variance reduction
- approximation methods
- posterior probability
- closed form
- methods in computer vision
- learning algorithm
- combining multiple
- adaboost algorithm
- boosting algorithms
- machine learning
- variational framework
- bayesian networks
- markov chain monte carlo
- optic flow
- gaussian process
- multiscale
- optical flow
- base classifiers
- sample size