#notuseful
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Looks like #google started fighting automatic #captcha recognition systems with adding noise to the images.
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Source: https://xkcd.com/2117/
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Efficient multi-lingual language model fine-tuning

Most of the worlds text is not in English. To enable researchers and practitioners to build impactful solutions in their domains, understanding how our NLP architectures fare in many languages needs to be more than an afterthought.
In this post, we introduce our latest paper that studies multilingual text classification and introduces #MultiFiT, a novel method based on #ULMFiT.

MultiFiT, trained on 100 labeled documents in the target language, outperforms multi-lingual BERT. It also outperforms the cutting-edge LASER algorithm-even though LASER requires a corpus of parallel texts, and MultiFiT does not.

Post: http://nlp.fast.ai/classification/2019/09/10/multifit.html
Paper: https://arxiv.org/abs/1909.04761
Tweet: https://twitter.com/seb_ruder/status/1186744388908654597?s=20

#NLP #DL #FineTuning
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FaceBoxes: A CPU Real-time Face Detector with High Accuracy. http://arxiv.org/abs/1708.05234
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Best paper at #KDD2017 idea: Android malware detection using API call relationships in a Machine-Learned system http://goo.gl/G7hGfC
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Best paper at #KDD2017 idea: Android malware detection using API call relationships in a Machine-Learned system http://goo.gl/G7hGfC
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Understanding and Comparing Deep Neural Networks for Age and Gender Classification. http://arxiv.org/abs/1708.07689
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Deep Learning In The Brain. #BigData #DeepLearning #MachineLearning #DataScience #AI #NeuroScience
https://buff.ly/2vuFkZy
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Learning to see through fog by synthetically adding fog to regular data. Evaluates on real foggy data. Useful in SF. https://arxiv.org/abs/1708.07819
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Neural network trained to rate how much pain someone is in just by looking at their face could
http://ow.ly/PfIw30eRLbD article:https://arxiv.org/abs/1708.04670
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ohai a machine learning system that can identify ~69% of protesters who are wearing caps AND scarfs to cover their face. Article: http://goo.gl/3nCuWU
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Machine Learning with TensorFlow (GDD Europe '17) https://buff.ly/2gGPKLr In this video, Andrew Gasparovic gives you an introduction to TensorFlow and goes through new things that have been developed
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BAIR blog post on our new NIPS paper on deep multi-view stereo. Check out how to train your stereo machine
http://bair.berkeley.edu/blog/2017/09/05/unified-3d/
Article:https://arxiv.org/abs/1708.05375
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Adversarial Discriminative Domain Adaptation" CVPR2017: combines discriminative modeling, weight sharing & GAN loss https://arxiv.org/abs/1702.05464
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