1 citations · 1 across the 5 of their papers we have counts for
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Feedback Coding for Active Learning
Gregory Canal, Matthieu Bloch, Christopher Rozell
The iterative selection of examples for labeling in active machine learning is conceptually similar to feedback channel coding in information theory: in both tasks, the objective i…
Variational Autoencoder with Learned Latent Structure
Marissa C. Connor, Gregory H. Canal, Christopher J. Rozell
The manifold hypothesis states that high-dimensional data can be modeled as lying on or near a low-dimensional, nonlinear manifold. Variational Autoencoders (VAEs) approximate this…
Representing Closed Transformation Paths in Encoded Network Latent Space
Marissa Connor, Christopher Rozell
Deep generative networks have been widely used for learning mappings from a low-dimensional latent space to a high-dimensional data space. In many cases, data transformations are d…
Active Ordinal Querying for Tuplewise Similarity Learning
Gregory Canal, Stefano Fenu, Christopher Rozell
Many machine learning tasks such as clustering, classification, and dataset search benefit from embedding data points in a space where distances reflect notions of relative similar…
Hierarchical Optimal Transport for Multimodal Distribution Alignment
John Lee, Max Dabagia, Eva L. Dyer +1
In many machine learning applications, it is necessary to meaningfully aggregate, through alignment, different but related datasets. Optimal transport (OT)-based approaches pose al…
Active embedding search via noisy paired comparisons
Gregory H. Canal, Andrew K. Massimino, Mark A. Davenport +1
Suppose that we wish to estimate a user's preference vector from paired comparisons of the form "does user prefer item or item ?," where both the user and items are…