Learning with Operator-valued Kernels in Reproducing Kernel Krein Spaces

1 code implementation • NeurIPS 2020 • Akash Saha, Balamurugan Palaniappan

A representer theorem is illustrated which yields a suitable loss stabilization problem for supervised learning with function-valued inputs and outputs.

Robust Discriminative Clustering with Sparse Regularizers

no code implementations • 29 Aug 2016 • Nicolas Flammarion, Balamurugan Palaniappan, Francis Bach

Clustering high-dimensional data often requires some form of dimensionality reduction, where clustered variables are separated from "noise-looking" variables.

Clustering Dimensionality Reduction