• MixMatch

• Referenced in 6 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...

• FastGCN

• Referenced in 7 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...

• 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...

• FixMatch

• Referenced in 2 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...

• ReMixMatch

• Referenced in 2 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...

• S4L

• Referenced in 1 article [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...

• 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...

• DivideMix

• Referenced in 1 article [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...

• BlinkFill

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

• RandAugment

• Referenced in 2 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...

• 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...

• DILS

• Referenced in 2 articles [sw38269]
• leading to a new kind of semi-supervised learning: constrained clustering. This technique...

• pomegranate

• Referenced in 1 article [sw26684]
• core learning, minibatch learning, and semi-supervised learning, without requiring the user to consider...