109 citations · 203 across the 22 of their papers we have counts for
41 papers
Estimating Rényi's -Cross-Entropies in a Matrix-Based Way
Isaac J. Sledge, Jose C. Principe
Conventional information-theoretic quantities assume access to probability distributions. Estimating such distributions is not trivial. Here, we consider function-based formulation…
Analysis of Intra-Operative Physiological Responses Through Complex Higher-Order SVD for Long-Term Post-Operative Pain Prediction
Raheleh Baharloo, Jose C. Principe, Parisa Rashidi +1
Long-term pain conditions after surgery and patients' responses to pain relief medications are not yet fully understood. While recent studies developed an index for nociception lev…
Uncertainty quantification for multiclass data description
Leila Kalantari, Jose Principe, Kathryn E. Sieving
In this manuscript, we propose a multiclass data description model based on kernel Mahalanobis distance (MDD-KM) with self-adapting hyperparameter setting. MDD-KM provides uncertai…
External-Memory Networks for Low-Shot Learning of Targets in Forward-Looking-Sonar Imagery
Isaac J. Sledge, Christopher D. Toole, Joseph A. Maestri +1
We propose a memory-based framework for real-time, data-efficient target analysis in forward-looking-sonar (FLS) imagery. Our framework relies on first removing non-discriminative…
An Information-Theoretic Approach for Automatically Determining the Number of States when Aggregating Markov Chains
Isaac J. Sledge, Jose C. Principe
A fundamental problem when aggregating Markov chains is the specification of the number of state groups. Too few state groups may fail to sufficiently capture the pertinent dynamic…
A Kernel Framework to Quantify a Model's Local Predictive Uncertainty under Data Distributional Shifts
Rishabh Singh, Jose C. Principe
Traditional Bayesian approaches for model uncertainty quantification rely on notoriously difficult processes of marginalization over each network parameter to estimate its probabil…