Learning Piecewise-Constant Functions to Classify and Cluster
Spring 2020
Master Diploma
Project: 00399
Classification and clustering are some of the most important objectives in supervised and unsupervised learning, respectively. Interestingly, in both scenarios, the learning scheme eventually produces a piecewise-constant function. This remarkable property allows one to analyze them jointly.
The goal of this project is to develop a variational framework to estimate piecewise-constant functions and to derive an efficient learning algorithm, built as a module. One can then also use this module in deep neural networks and compare the performance with classical setups for various applications of classification and clustering.
- Supervisors
- Shayan Aziznejad, shayan. aziznejad@epfl.ch, BM 4.138
- Michael Unser, michael.unser@epfl.ch, 021 693 51 75, BM 4.136