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Found 6 papers, 2 papers with code
Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN Design
In this paper, we present a novel fully hyperbolic neural network which uses the concept of projections (embeddings) followed by an intrinsic aggregation and a nonlinearity all within the hyperbolic space.
Nested Grassmannians for Dimensionality Reduction with Applications
With the proposed NG structure, we develop algorithms for the supervised and unsupervised dimensionality reduction problems respectively.
MVC-Net: A Convolutional Neural Network Architecture for Manifold-Valued Images With Applications
Our goal in this paper is to generalize convolutional neural networks (CNN) to the manifold-valued image case which arises commonly in medical imaging and computer vision applications.
A mixture model for aggregation of multiple pre-trained weak classifiers
The other alternative to increase the performance is to learn multiple weak classifiers and boost their performance using a boosting algorithm or a variant thereof.
A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices
We show how recurrent statistical recurrent network models can be defined in such spaces.
Multiple-Instance Logistic Regression with LASSO Penalty
In this work, we consider a manufactory process which can be described by a multiple-instance logistic regression model.
