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Farnoosh Ghadiri

Alumni

Publications

On Adversarial Mixup Resynthesis
Christopher Beckham
Sina Honari
Alex Lamb
Vikas Verma
Farnoosh Ghadiri
R Devon Hjelm
Yoshua Bengio
Christopher Pal
In this paper, we explore new approaches to combining information encoded within the learned representations of auto-encoders. We explore mo… (voir plus)dels that are capable of combining the attributes of multiple inputs such that a resynthesised output is trained to fool an adversarial discriminator for real versus synthesised data. Furthermore, we explore the use of such an architecture in the context of semi-supervised learning, where we learn a mixing function whose objective is to produce interpolations of hidden states, or masked combinations of latent representations that are consistent with a conditioned class label. We show quantitative and qualitative evidence that such a formulation is an interesting avenue of research.
2019-03-06
Neural Information Processing Systems (publié)
dblp.uni-trier.de
Adversarial Mixup Resynthesizers
Christopher Beckham
Sina Honari
Alex Lamb
Vikas Verma
Farnoosh Ghadiri
R Devon Hjelm
Christopher Pal
In this paper, we explore new approaches to combining information encoded within the learned representations of autoencoders. We explore mod… (voir plus)els that are capable of combining the attributes of multiple inputs such that a resynthesised output is trained to fool an adversarial discriminator for real versus synthesised data. Furthermore, we explore the use of such an architecture in the context of semi-supervised learning, where we learn a mixing function whose objective is to produce interpolations of hidden states, or masked combinations of latent representations that are consistent with a conditioned class label. We show quantitative and qualitative evidence that such a formulation is an interesting avenue of research.
2018-12-31
DGS@ICLR (publié)
openreview.net
openreview.net