4 papers · 1 filter
Slow Feature Analysis on Markov Chains from Goal-Directed Behavior
Merlin Schüler, Eddie Seabrook, Laurenz Wiskott
Slow Feature Analysis is a unsupervised representation learning method that extracts slowly varying features from temporal data and can be used as a basis for subsequent reinforcem…
Slow Feature Analysis as Variational Inference Objective
Merlin Schüler, Laurenz Wiskott
This work presents a novel probabilistic interpretation of Slow Feature Analysis (SFA) through the lens of variational inference. Unlike prior formulations that recover linear SFA…
Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening
Merlin Schüler, Hlynur Davíð Hlynsson, Laurenz Wiskott
We propose Power Slow Feature Analysis, a gradient-based method to extract temporally slow features from a high-dimensional input stream that varies on a faster time-scale, as a va…
Dual SVM Training on a Budget
Sahar Qaadan, Merlin Schüler, Tobias Glasmachers
We present a dual subspace ascent algorithm for support vector machine training that respects a budget constraint limiting the number of support vectors. Budget methods are effecti…