6 citations · 12 across the 3 of their papers we have counts for
6 papers
Making Sense Of Distributed Representations With Activation Spectroscopy
Kyle Reing, Greg Ver Steeg, Aram Galstyan
In the study of neural network interpretability, there is growing evidence to suggest that relevant features are encoded across many neurons in a distributed fashion. Making sense…
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights
Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg +1
In the presence of noisy or incorrect labels, neural networks have the undesirable tendency to memorize information about the noise. Standard regularization techniques such as drop…
Maximizing Multivariate Information with Error-Correcting Codes
Kyle Reing, Greg Ver Steeg, Aram Galstyan
Multivariate mutual information provides a conceptual framework for characterizing higher-order interactions in complex systems. Two well-known measures of multivariate information…
Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge
Ryan J. Gallagher, Kyle Reing, David Kale +1
While generative models such as Latent Dirichlet Allocation (LDA) have proven fruitful in topic modeling, they often require detailed assumptions and careful specification of hyper…
Toward Interpretable Topic Discovery via Anchored Correlation Explanation
Kyle Reing, David C. Kale, Greg Ver Steeg +1
Many predictive tasks, such as diagnosing a patient based on their medical chart, are ultimately defined by the decisions of human experts. Unfortunately, encoding experts' knowled…
Sifting Common Information from Many Variables
Greg Ver Steeg, Shuyang Gao, Kyle Reing +1
Measuring the relationship between any pair of variables is a rich and active area of research that is central to scientific practice. In contrast, characterizing the common inform…