• EMCluster

  • Referenced in 6 articles [sw24496]
  • dispersion in both of unsupervised and semi-supervised learning...
  • 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 4 articles [sw23902]
  • state-of-the-art performance for semi-supervised learning, for clustering or classification. We present...
  • RALF

  • Referenced in 3 articles [sw33955]
  • part of the project Semi-supervised learning in image collections. This framework combines active learning...
  • PTE

  • Referenced in 5 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...
  • FastGCN

  • Referenced in 3 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...
  • pomegranate

  • Referenced in 2 articles [sw26684]
  • core learning, minibatch learning, and semi-supervised learning, without requiring the user to consider...
  • 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...
  • GBFlearn

  • Referenced in 2 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...
  • BlinkFill

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

  • Referenced in 2 articles [sw36514]
  • from Internet data. NEIL uses a semi-supervised learning algorithm that jointly discovers common sense...
  • InfoGraph

  • Referenced in 2 articles [sw37754]
  • InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization. This paper ... studies learning the representations of whole graphs in both unsupervised and semi-supervised scenarios. Graph ... semi-supervised scenarios. InfoGraph* maximizes the mutual information between unsupervised graph representations learned by InfoGraph ... representations learned by existing supervised methods. As a result, the supervised encoder learns from unlabeled...
  • GraphDemo

  • Referenced in 1 article [sw10148]
  • their use in machine learning. Many machine learning algorithms model local neighborhoods using similarity graphs ... denoising, spectral clustering, label propagation for semi-supervised learning, and so on. However, for most...
  • OLALA

  • Referenced in 1 article [sw38125]
  • inefficient. These characteristics also challenge existing active learning methods, as image-level scoring and selection ... common objects.Inspired by recent progresses in semi-supervised learning and self-training, we propose...
  • CLEMM

  • Referenced in 1 article [sw31323]
  • learning technique in multivariate statistics and machine learning. In this paper, we propose ... envelope methods in unsupervised and semi-supervised learning problems. Numerical studies on simulated data...
  • DILS

  • Referenced in 1 article [sw38269]
  • leading to a new kind of semi-supervised learning: constrained clustering. This technique...
  • DeepAffinity

  • Referenced in 1 article [sw39160]
  • structurally-annotated protein sequences, a semi-supervised deep learning model that unifies recurrent and convolutional...
  • MEKA

  • Referenced in 13 articles [sw15429]
  • variety of methods for this type of learning. We present MEKA: an open-source Java ... target data, including in incremental and semi-supervised contexts...
  • Manifold Regularization

  • Referenced in 1 article [sw24840]
  • marginal distribution. We focus on a semi-supervised framework that incorporates labeled and unlabeled data ... handle both transductive and truly semi-supervised settings. We present experimental evidence suggesting that ... semi-supervised algorithms are able to use unlabeled data effectively. Finally we have a brief ... discussion of unsupervised and fully supervised learning within our general framework...