• MixMatch

  • Referenced in 10 articles [sw41280]
  • Mixmatch: A holistic approach to semi-supervised learning. Semi-supervised learning has proven ... unify the current dominant approaches for semi-supervised learning to produce a new algorithm, MixMatch...
  • SemiBoost

  • Referenced in 7 articles [sw43049]
  • SemiBoost: Boosting for Semi-Supervised Learning. Semi-supervised learning has attracted a significant amount ... present a boosting framework for semi-supervised learning, termed as SemiBoost. The key advantages ... proposed semi-supervised learning approach are: 1) performance improvement of any supervised learning algorithm with ... state-of-the-art semi-supervised learning algorithms...
  • FastGCN

  • Referenced in 9 articles [sw38089]
  • FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. The graph convolutional networks ... effective graph model for semi-supervised learning. This model, however, was originally designed...
  • FixMatch

  • Referenced in 4 articles [sw41277]
  • FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. Semi-supervised learning (SSL) provides ... performance across a variety of standard semi-supervised learning benchmarks, including 94.93% accuracy on CIFAR...
  • S4L

  • Referenced in 3 articles [sw41278]
  • Self-Supervised Semi-Supervised Learning. This work tackles the problem of semi-supervised learning ... insight is that the field of semi-supervised learning can benefit from the quickly advancing ... propose the framework of self-supervised semi-supervised learning and use it to derive ... both carefully tuned baselines, and existing semi-supervised learning methods. We then show that...
  • ReMixMatch

  • Referenced in 4 articles [sw41275]
  • ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring. We improve the recently-proposed ... MixMatch” semi-supervised learning algorithm by introducing two new techniques: distribution alignment and augmentation anchoring...
  • EMCluster

  • Referenced in 6 articles [sw24496]
  • dispersion in both of unsupervised and semi-supervised learning...
  • GANomaly

  • Referenced in 5 articles [sw41240]
  • GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training. Anomaly detection is a classical problem ... this can be addressed as a supervised learning problem, a significantly more challenging problem ... space of a one-class, semi-supervised learning paradigm. We introduce such a novel anomaly...
  • Spider

  • Referenced in 8 articles [sw10713]
  • spider - machine learning toolbox for Matlab. It’s a library of objects in Matlab ... reasonably) large unsupervised, supervised or semi-supervised machine learning problems. Aims to become a complete...
  • DIFFRAC

  • Referenced in 5 articles [sw23902]
  • state-of-the-art performance for semi-supervised learning, for clustering or classification. We present...
  • PTE

  • Referenced in 7 articles [sw37756]
  • task. Although the low dimensional representations learned are applicable to many different tasks, they ... this gap by proposing a semi-supervised representation learning method for text data, which...
  • GBFlearn

  • Referenced in 4 articles [sw36067]
  • GBFlearn - Learning with Graph Basis Functions. A very simple toolbox to illustrate how graph basis ... used for interpolation, classification and semi-supervised learning on graphs...
  • RALF

  • Referenced in 4 articles [sw33955]
  • part of the project Semi-supervised learning in image collections. This framework combines active learning...
  • DivideMix

  • Referenced in 2 articles [sw42305]
  • DivideMix: Learning with Noisy Labels as Semi-supervised Learning. Deep neural networks are known ... include learning with noisy labels and semi-supervised learning by exploiting unlabeled data. In this ... learning with noisy labels by leveraging semi-supervised learning techniques. In particular, DivideMix models ... labeled and unlabeled data in a semi-supervised manner. To avoid confirmation bias, we simultaneously...
  • RandAugment

  • Referenced in 4 articles [sw40532]
  • significantly improve the generalization of deep learning models. Recently, automated augmentation strategies have ... state-of-the-art results in semi-supervised learning and improved robustness to common corruptions...
  • FlexMatch

  • Referenced in 2 articles [sw43050]
  • FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling. The recently proposed FixMatch achieved state ... results on most semi-supervised learning (SSL) benchmarks. However, like other modern SSL algorithms, FixMatch...
  • VoxPopuli

  • Referenced in 1 article [sw39143]
  • Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation. We introduce VoxPopuli ... unsupervised representation learning as well as semi-supervised learning. VoxPopuli also contains 1.8K hours ... versatility of VoxPopuli unlabelled data in semi-supervised learning under challenging out-of-domain settings...
  • BlinkFill

  • Referenced in 2 articles [sw29485]
  • large space. We present a semi-supervised learning technique to significantly reduce this ambiguity...
  • GraphLearning

  • Referenced in 1 article [sw42962]
  • graph-based learning algorithms for both semi-supervised learning and clustering. The package implements many ... Slepcev. Poisson Learning: Graph Based Semi-Supervised Learning at Very Low Label Rates., Proceedings...
  • salad

  • Referenced in 1 article [sw39362]
  • Salad: A Toolbox for Semi-supervised Adaptive Learning Across Domains. We introduce salad, an open ... methods for transfer learning, semi-supervised learning and domain adaptation. In the first release...