458 citations · 893 across the 37 of their papers we have counts for
7 papers · 1 filter
Learning Sinkhorn divergences for supervised change point detection
Nauman Ahad, Eva L. Dyer, Keith B. Hengen +2
Many modern applications require detecting change points in complex sequential data. Most existing methods for change point detection are unsupervised and, as a consequence, lack a…
Active metric learning and classification using similarity queries
Namrata Nadagouda, Austin Xu, Mark A. Davenport
Active learning is commonly used to train label-efficient models by adaptively selecting the most informative queries. However, most active learning strategies are designed to eith…
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time
Feng Zhu, Andrew R. Sedler, Harrison A. Grier +5
Modern neural interfaces allow access to the activity of up to a million neurons within brain circuits. However, bandwidth limits often create a trade-off between greater spatial s…
Semi-supervised sequence classification through change point detection
Nauman Ahad, Mark A. Davenport
Sequential sensor data is generated in a wide variety of practical applications. A fundamental challenge involves learning effective classifiers for such sequential data. While dee…
Generative causal explanations of black-box classifiers
Matthew O'Shaughnessy, Gregory Canal, Marissa Connor +2
We develop a method for generating causal post-hoc explanations of black-box classifiers based on a learned low-dimensional representation of the data. The explanation is causal in…
A unified framework for manifold landmarking
Hongteng Xu, Licheng Yu, Mark Davenport +1
The success of semi-supervised manifold learning is highly dependent on the quality of the labeled samples. Active manifold learning aims to select and label representative landmar…
A Theoretical Analysis of Joint Manifolds
Mark A. Davenport, Chinmay Hegde, Marco F. Duarte +1
The emergence of low-cost sensor architectures for diverse modalities has made it possible to deploy sensor arrays that capture a single event from a large number of vantage points…