activity
20192022
most citedActive embedding search via noisy paired comparisons

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

eess.SP2022

A Low-complexity Brain-computer Interface for High-complexity Robot Swarm Control

Gregory Canal, Yancy Diaz-Mercado, Magnus Egerstedt +1

A brain-computer interface (BCI) is a system that allows a human operator to use only mental commands in controlling end effectors that interact with the world around them. Such a…

stat.ML2021

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…

cs.LG2020

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…

stat.ML2020

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…

stat.ML2019

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…

stat.ML20191 cited

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…