101 citations · 151 across the 18 of their papers we have counts for
4 papers · 2 filters
Discovery and Separation of Features for Invariant Representation Learning
Ayush Jaiswal, Rob Brekelmans, Daniel Moyer +3
Supervised machine learning models often associate irrelevant nuisance factors with the prediction target, which hurts generalization. We propose a framework for training robust ne…
Invariant Representations through Adversarial Forgetting
Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg +2
We propose a novel approach to achieving invariance for deep neural networks in the form of inducing amnesia to unwanted factors of data through a new adversarial forgetting mechan…
Efficient Covariance Estimation from Temporal Data
Hrayr Harutyunyan, Daniel Moyer, Hrant Khachatrian +2
Estimating the covariance structure of multivariate time series is a fundamental problem with a wide-range of real-world applications -- from financial modeling to fMRI analysis. D…
Exact Rate-Distortion in Autoencoders via Echo Noise
Rob Brekelmans, Daniel Moyer, Aram Galstyan +1
Compression is at the heart of effective representation learning. However, lossy compression is typically achieved through simple parametric models like Gaussian noise to preserve…