An ensemble diversity approach to supervised binary hashing.
Miguel Á. Carreira-PerpiñánRamin RaziperchikolaeiPublished in: NIPS (2016)
Keyphrases
- hamming distance
- classifier ensemble
- gray code
- learning algorithm
- binary codes
- ensemble members
- feature selection
- hamming space
- ensemble learning
- locality sensitive
- diversity measures
- supervised learning
- ensemble methods
- neural network
- machine learning
- data structure
- training set
- base classifiers
- random forest
- random forests
- random projections
- supervised classification
- randomized trees
- non binary
- ensemble classifier
- file organization
- data sets
- index structure
- pairwise
- locality sensitive hashing
- binary classification problems
- majority voting
- support vector machine
- semi supervised
- regression problems
- principal component analysis
- unsupervised learning