28 citations · 85 across the 14 of their papers we have counts for
14 papers
Weakly-Supervised Semantic Segmentation of Circular-Scan, Synthetic-Aperture-Sonar Imagery
Isaac J. Sledge, Dominic M. Byrne, Jonathan L. King +6
We propose a weakly-supervised framework for the semantic segmentation of circular-scan synthetic-aperture-sonar (CSAS) imagery. The first part of our framework is trained in a sup…
Adapting the Exploration Rate for Value-of-Information-Based Reinforcement Learning
Isaac J. Sledge, Jose C. Principe
In this paper, we consider the problem of adjusting the exploration rate when using value-of-information-based exploration. We do this by converting the value-of-information optimi…
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…
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…
Annotating Motion Primitives for Simplifying Action Search in Reinforcement Learning
Isaac J. Sledge, Darshan W. Bryner, Jose C. Principe
Reinforcement learning in large-scale environments is challenging due to the many possible actions that can be taken in specific situations. We have previously developed a means of…