649 citations
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7 papers · 2 filters
Data Distillation: Towards Omni-Supervised Learning
Ilija Radosavovic, Piotr Dollár, Ross Girshick +2
We investigate omni-supervised learning, a special regime of semi-supervised learning in which the learner exploits all available labeled data plus internet-scale sources of unlabe…
Countering Adversarial Images using Input Transformations
Chuan Guo, Mayank Rana, Moustapha Cisse +1
This paper investigates strategies that defend against adversarial-example attacks on image-classification systems by transforming the inputs before feeding them to the system. Spe…
Efficient K-Shot Learning with Regularized Deep Networks
Donghyun Yoo, Haoqi Fan, Vishnu Naresh Boddeti +1
Feature representations from pre-trained deep neural networks have been known to exhibit excellent generalization and utility across a variety of related tasks. Fine-tuning is by f…
One-Sided Unsupervised Domain Mapping
Sagie Benaim, Lior Wolf
In unsupervised domain mapping, the learner is given two unmatched datasets and . The goal is to learn a mapping that translates a sample in to the analog sampl…
Fader Networks: Manipulating Images by Sliding Attributes
Guillaume Lample, Neil Zeghidour, Nicolas Usunier +3
This paper introduces a new encoder-decoder architecture that is trained to reconstruct images by disentangling the salient information of the image and the values of attributes di…
BARCHAN: Blob Alignment for Robust CHromatographic ANalysis
Camille Couprie, Laurent Duval, Maxime Moreaud +3
Comprehensive Two dimensional gas chromatography (GCxGC) plays a central role into the elucidation of complex samples. The automation of the identification of peak areas is of prim…