7 accepted papers
Decision tree ensembles are widely used in critical domains, making robustness and sensitivity analysis essential to their trustworthiness. We study the feature sensitivity problem, which asks whether an ensemble is ``sensitive" to a specified subset of features - such as protected attributes- whose…
Tree ensemble models, such as Gradient Boosted Decision Trees (GBDTs) and random forests, are widely popular models for a variety of machine learning tasks. The power of these models comes from the ensemble of decision trees, which makes analysis of such models significantly harder than for single t…
Payload transport over flat terrain via multi-wheel robot carriers is well-understood, highly effective, and configurable. In this paper, our goal is to provide similar effectiveness and configurability for transport over rough terrain that is more suitable for legs rather than wheels. For this purp…
Ultrasound scanning is an efficient imaging modality preferred for quick medical procedures. However, due to the lack of skilled sonographers, researchers have developed many Robotic Ultrasound System (RUS) prototypes for various procedures. Most of these systems have a human-in-the-loop and require…
As the complexity of pacemaker devices continues to grow, the importance of capturing its functional correctness requirement formally cannot be overestimated. The pacemaker system specification document by \emph{Boston Scientific} provides a widely accepted set of specifications for pacemakers. As…
In a structural collapse, debris piles up in a chaotic and unstable manner, creating pockets and void spaces that are difficult to see or access. Often, these regions have the highest chances of concealing survivors and identifying such regions can increase the success of a search and rescue (SAR) o…
In this paper, we propose methods to compute confidence score on the predictions made by an end-to-end speech recognition model in a 2-pass framework. We use RNN-Transducer for a streaming model, and an attention-based decoder for the second pass model. We use neural technique to compute the confide…