High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning.
Antoine GrosnitRasul TutunovAlexandre Max MaravalRyan-Rhys GriffithsAlexander Imani Cowen-RiversLin YangLin ZhuWenlong LyuZhitang ChenJun WangJan PetersHaitham Bou-AmmarPublished in: CoRR (2021)
Keyphrases
- metric learning
- high dimensional
- dimensionality reduction
- feature space
- distance metric learning
- distance metric
- low dimensional
- denoising
- machine learning and pattern recognition
- pairwise
- semi supervised
- high dimensional data
- learning tasks
- data points
- distance function
- semi supervised clustering
- similarity search
- unsupervised learning
- mahalanobis metric
- manifold learning
- input space
- multi task
- kernel function
- maximum likelihood
- nearest neighbor
- subject to linear constraints
- semi supervised learning
- feature extraction
- euclidean distance
- transfer learning
- model selection
- markov random field
- multi class
- feature vectors
- pattern recognition
- gaussian processes
- image segmentation
- decision trees
- feature selection
- data mining