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zero-shot super-resolution using deep internal learning assaf shocher nadav cohen michal irani dept. of computer science and applied math, the weizmann
1. roelof pieters zero-shot learning through cross-modal transfer 20 february 2015 deep learning reading group richard socher,
multimodal deep learning zeynep akata zero-shot learning latent embeddings for zero-shot image classification xian et.al., cvpr16 & cvpr17 w large error w w
1. hubness and pollution: delving into cross-space mapping for zero-shot learning angeliki lazaridou, georgiana dinu, marco baroni acl-ijcnlp 2015
darla: improving zero-shot transfer in reinforcement learning irina higgins * 1 arka pal * 1 andrei rusu 1 loic matthey 1 christopher burgess 1 alexander pritzel 1 matthew
one shot learning sk telecom video tech. lab. manager contents why do we need one-shot learning? what is one-shot learning? how to do one-shot learning recap
semantically consistent regularization for zero-shot recognition pedro morgado nuno vasconcelos department of electrical and computer engineering university of california,
powerpoint presentation one-shot learning gesture recognition students: itay hubara amit nishry supervisor: maayan harel gal-on outline 2 background gesture recognition is
one-shot learning with memory-augmented neural networks adam santoro adamsantoro@google.com google deepmind sergey bartunov sbos@sbos.in google deepmind, national research
jmlr: workshop and conference proceedings 27:195207, 2012 workshop on unsupervised and transfer learning one-shot learning with a hierarchical nonparametric bayesian model
1. learning zonexpressyour source for innovative nutrition education and life skills productspresentsflu shot stickers 2.
matching networks for one shot learning oriol vinyals google deepmind vinyals@google.com charles blundell google deepmind cblundell@google.com timothy lillicrap google deepmind
1. googles multilingual neural machine translation system: enabling zero-shot translation melvin johnson, mike schuster, quoc v. le, maxim krikun, yonghui wu, zhifeng
one shot learning via compositions of meaningful patches alex wong university of california, los angeles alexw@cs.ucla.edu alan yuille university of california, los angeles
copyright (c) dena co.,ltd. all rights reserved. ai system dept. system management unit kazuki fujikawa matching networks for one shot learning https://papers.nips.cc/paper/6385-matching-networks-for-one-
costa: co-occurrence statistics for zero-shot classification thomas mensink university of amsterdam parts & attributes workshop eccv 2014 september 12th parts
powerpoint presentation zero-shot learning by convex combination of semantic embeddings mohammad norouzi, tomas mikolov, samy bengio, yoram singer, jonathon shlens, andrea
1. learning from nature beyond carbon zero francesca galeazziarup associatesgreen drinksshanghai11 october 2012 2. arup and arup
a mitsubishi zero shot dovvn at pearl harbor revealed surprisingly fevv facts about the mysterious fighter, but did yield a map that provided tantalizing clues about the
shaban, bansal, liu, essa, boots: one-shot semantic segmentation 1 one-shot learning for semantic segmentation amirreza shaban amirreza@gatech.edu shray bansal sbansal34@gatech.edu