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cs.LG2019
Unsupervised Domain Adaptation via Regularized Conditional Alignment
Safa Cicek, Stefano Soatto
We propose a method for unsupervised domain adaptation that trains a shared embedding to align the joint distributions of inputs (domain) and outputs (classes), making any classifi…
cs.LG2018
Input and Weight Space Smoothing for Semi-supervised Learning
Safa Cicek, Stefano Soatto
We propose regularizing the empirical loss for semi-supervised learning by acting on both the input (data) space, and the weight (parameter) space. We show that the two are not equ…