41 citations · 139 across the 12 of their papers we have counts for
14 papers
LUMÁWIG: An Efficient Algorithm for Dimension Zero Bottleneck Distance Computation in Topological Data Analysis
Paul Samuel Ignacio, Jay-Anne Bulauan, David Uminsky
Stability of persistence diagrams under slight perturbations is a key characteristic behind the validity and growing popularity of topological data analysis in exploring real-world…
Identifying group contributions in NBA lineups with spectral analysis
Stephen Devlin, David Uminsky
We address the question of how to quantify the contributions of groups of players to team success. Our approach is based on spectral analysis, a technique from algebraic signal pro…
The Problem with Metrics is a Fundamental Problem for AI
Rachel Thomas, David Uminsky
Optimizing a given metric is a central aspect of most current AI approaches, yet overemphasizing metrics leads to manipulation, gaming, a myopic focus on short-term goals, and othe…
Classification of Single-lead Electrocardiograms: TDA Informed Machine Learning
Paul Samuel Ignacio, David Uminsky, Christopher Dunstan +2
Atrial Fibrillation is a heart condition characterized by erratic heart rhythms caused by chaotic propagation of electrical impulses in the atria, leading to numerous health compli…
A Non-iterative Parallelizable Eigenbasis Algorithm for Johnson Graphs
Jackson Abascal, Amadou Bah, Mario Banuelos +2
We present a new method for generating an orthogonal basis of eigenvectors for the Johnson graph . Unlike standard methods for computing a full eige…
The power of A/B testing under interference
James D. Wilson, David T. Uminsky
In this paper, we address the fundamental statistical question: how can you assess the power of an A/B test when the units in the study are exposed to interference? This question i…