630 citations · 1.7k across the 6 of their papers we have counts for
8 papers
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman, Eric Tzeng, Taesung Park +5
Domain adaptation is critical for success in new, unseen environments. Adversarial adaptation models applied in feature spaces discover domain invariant representations, but are di…
Label Efficient Learning of Transferable Representations across Domains and Tasks
Zelun Luo, Yuliang Zou, Judy Hoffman +1
We propose a framework that learns a representation transferable across different domains and tasks in a label efficient manner. Our approach battles domain shift with a domain adv…
VisDA: The Visual Domain Adaptation Challenge
Xingchao Peng, Ben Usman, Neela Kaushik +3
We present the 2017 Visual Domain Adaptation (VisDA) dataset and challenge, a large-scale testbed for unsupervised domain adaptation across visual domains. Unsupervised domain adap…
Multiple-Source Adaptation for Regression Problems
Judy Hoffman, Mehryar Mohri, Ningshan Zhang
We present a detailed theoretical analysis of the problem of multiple-source adaptation in the general stochastic scenario, extending known results that assume a single target labe…
Fine-grained Recognition in the Wild: A Multi-Task Domain Adaptation Approach
Timnit Gebru, Judy Hoffman, Li Fei-Fei
While fine-grained object recognition is an important problem in computer vision, current models are unlikely to accurately classify objects in the wild. These fully supervised mod…
Inferring and Executing Programs for Visual Reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten +4
Existing methods for visual reasoning attempt to directly map inputs to outputs using black-box architectures without explicitly modeling the underlying reasoning processes. As a r…