AdaBoost on low-rank PSD matrices for metric learning.
Jinbo BiDijia WuLe LuMeizhu LiuYimo TaoMatthias WolfPublished in: CVPR (2011)
Keyphrases
- metric learning
- low rank
- semi supervised
- matrix completion
- low rank matrix
- singular value decomposition
- positive semidefinite
- dimensionality reduction
- kernel matrix
- singular values
- eigendecomposition
- distance metric
- missing data
- matrix factorization
- convex optimization
- pairwise
- multi class
- learning algorithm
- multi task
- object detection
- high dimensional data
- distance function
- semi supervised learning
- learning tasks
- linear combination
- training data
- active learning
- feature space
- labeled data
- unsupervised learning
- support vector
- boosting algorithms
- high order
- manifold learning
- knn
- high dimensional
- data points
- feature selection
- principal component analysis
- data sets
- decision trees
- interior point methods
- multiple kernel learning
- pattern recognition
- supervised learning
- similarity search
- low dimensional