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Beating the state-of-the-art with one-shot learning is not common. Transfer learning for NLP is also quite unchartered. Also the technique is quite novel: This
by Danylon 10y ago
Beating the state-of-the-art with one-shot learning is not common. Transfer learning for NLP is also quite unchartered.
Also the technique is quite novel: This is not pre-trained nets on labeled data, it is an unsupervised generative model.
Future research directions are exciting: Unsupervised prediction of the next frame in a video, and then being able to one-shot learn a wide range of visual tasks.
- kastnerkyle 9y agoYou might be interested in minute 50 onward [0], or this recent paper from Facebook [1]. [0] https://www.youtube.com/watch?v=-yX1SYeDHbg&list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu&index=4 https://www.youtube.com/watch?v=-yX1SYeDHbg&list=PLE6Wd9FR--... [1] https://arxiv.org/abs/1703.07684 https://arxiv.org/abs/1703.07684
- Danylon 9y agoCool. I knew of previous work [1], but not the recent paper you posted. Thanks. [1] https://arxiv.org/abs/1412.6056 https://arxiv.org/abs/1412.6056 "Predicting Deeper into the Future of Semantic Segmentation"