5 citations · 7 across the 5 of their papers we have counts for
5 papers
A Family of Kernelized Matrix Costs for Multiple-Output Mixture Neural Networks
Bo Hu, José C. Príncipe
Pairwise distance-based costs are crucial for self-supervised and contrastive feature learning. Mixture Density Networks (MDNs) are a widely used approach for generative models and…
Kernel Operator-Theoretic Bayesian Filter for Nonlinear Dynamical Systems
Kan Li, José C. Príncipe
Motivated by the surge of interest in Koopman operator theory, we propose a machine-learning alternative based on a functional Bayesian perspective for operator-theoretic modeling…
Feature Learning in Image Hierarchies using Functional Maximal Correlation
Bo Hu, Yuheng Bu, José C. Príncipe
This paper proposes the Hierarchical Functional Maximal Correlation Algorithm (HFMCA), a hierarchical methodology that characterizes dependencies across two hierarchical levels in…
The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making
Shujian Yu, Hongming Li, Sigurd Løkse +2
The Cauchy-Schwarz (CS) divergence was developed by Príncipe et al. in 2000. In this paper, we extend the classic CS divergence to quantify the closeness between two conditional di…
Concept Drift Detection and Adaptation with Hierarchical Hypothesis Testing
Shujian Yu, Zubin Abraham, Heng Wang +3
A fundamental issue for statistical classification models in a streaming environment is that the joint distribution between predictor and response variables changes over time (a ph…