{
  "id": 135164,
  "title": "\"Less Label, More Learning\"",
  "url": "/competitions/bengaliai-cv19/discussion/135164",
  "author_name": "FGPC",
  "post_date": "2020-03-12T11:11:09.883000",
  "votes": 1,
  "comment_count": 0,
  "views": 0,
  "content": "<p>An important topic you might try to experiment especially on \"Less Label, More Learning\"</p>\n\n<p><a href=\"https://blog.deeplearning.ai/blog/the-batch-mind-controlled-robot-hand-fashions-by-gan-face-recognition-countermeasure-more-realistic-deepfakes-learning-from-unlabeled-data\">https://blog.deeplearning.ai/blog/the-batch-mind-controlled-robot-hand-fashions-by-gan-face-recognition-countermeasure-more-realistic-deepfakes-learning-from-unlabeled-data</a></p>\n\n<p>FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence: <a href=\"https://arxiv.org/abs/2001.07685\">https://arxiv.org/abs/2001.07685</a></p>\n\n<p>Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning: <a href=\"https://arxiv.org/abs/1606.04586\">https://arxiv.org/abs/1606.04586</a></p>\n\n<p>RandAugment: Practical automated data augmentation with a reduced search space: <a href=\"https://arxiv.org/abs/1909.13719\">https://arxiv.org/abs/1909.13719</a></p>\n\n<p>ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring: <a href=\"https://arxiv.org/abs/1911.09785\">https://arxiv.org/abs/1911.09785</a></p>",
  "messages": [
    {
      "id": 769887,
      "postDate": "2020-03-12T11:11:09.883Z",
      "content": "<p>An important topic you might try to experiment especially on \"Less Label, More Learning\"</p>\n\n<p><a href=\"https://blog.deeplearning.ai/blog/the-batch-mind-controlled-robot-hand-fashions-by-gan-face-recognition-countermeasure-more-realistic-deepfakes-learning-from-unlabeled-data\">https://blog.deeplearning.ai/blog/the-batch-mind-controlled-robot-hand-fashions-by-gan-face-recognition-countermeasure-more-realistic-deepfakes-learning-from-unlabeled-data</a></p>\n\n<p>FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence: <a href=\"https://arxiv.org/abs/2001.07685\">https://arxiv.org/abs/2001.07685</a></p>\n\n<p>Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning: <a href=\"https://arxiv.org/abs/1606.04586\">https://arxiv.org/abs/1606.04586</a></p>\n\n<p>RandAugment: Practical automated data augmentation with a reduced search space: <a href=\"https://arxiv.org/abs/1909.13719\">https://arxiv.org/abs/1909.13719</a></p>\n\n<p>ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring: <a href=\"https://arxiv.org/abs/1911.09785\">https://arxiv.org/abs/1911.09785</a></p>",
      "rawMarkdown": "An important topic you might try to experiment especially on \"Less Label, More Learning\"\n\nhttps://blog.deeplearning.ai/blog/the-batch-mind-controlled-robot-hand-fashions-by-gan-face-recognition-countermeasure-more-realistic-deepfakes-learning-from-unlabeled-data\n\nFixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence: https://arxiv.org/abs/2001.07685\n\nRegularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning: https://arxiv.org/abs/1606.04586\n\nRandAugment: Practical automated data augmentation with a reduced search space: https://arxiv.org/abs/1909.13719\n\nReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring: https://arxiv.org/abs/1911.09785",
      "votes": 1
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "769887": "An important topic you might try to experiment especially on \"Less Label, More Learning\"\n\nhttps://blog.deeplearning.ai/blog/the-batch-mind-controlled-robot-hand-fashions-by-gan-face-recognition-countermeasure-more-realistic-deepfakes-learning-from-unlabeled-data\n\nFixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence: https://arxiv.org/abs/2001.07685\n\nRegularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning: https://arxiv.org/abs/1606.04586\n\nRandAugment: Practical automated data augmentation with a reduced search space: https://arxiv.org/abs/1909.13719\n\nReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring: https://arxiv.org/abs/1911.09785"
  }
}