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Found 5 papers, 1 papers with code
Adaptive Clustering Using Kernel Density Estimators
We derive and analyze a generic, recursive algorithm for estimating all splits in a finite cluster tree as well as the corresponding clusters.
liquidSVM: A Fast and Versatile SVM package
liquidSVM is a package written in C++ that provides SVM-type solvers for various classification and regression tasks.
Learning with Hierarchical Gaussian Kernels
We investigate iterated compositions of weighted sums of Gaussian kernels and provide an interpretation of the construction that shows some similarities with the architectures of deep neural networks.
Spatial Decompositions for Large Scale SVMs
Our contributions are two fold: On the theoretical side we establish an oracle inequality for the overall learning method using the hinge loss, and show that the resulting rates match those known for SVMs solving the complete optimization problem with Gaussian kernels.
Towards an Axiomatic Approach to Hierarchical Clustering of Measures
We propose some axioms for hierarchical clustering of probability measures and investigate their ramifications.
