Who Cited It

Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples

2006 · 3,266 citations · 8 from inside this corpus

Mikhail Belkin, Partha Niyogi, Vikas Sindhwani low

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Ex… (2006)Manifold Regularization: A Ge…Statistical Learning Theory (1999)Statistical Learning TheoryCombining labeled and unlabeled data with co-training (1998)Combining labeled and unlabel…Semi-Supervised Learning (2006)Semi-Supervised LearningLearning with Local and Global Consistency (2003)Learning with Local and Globa…Text Classification from Labeled and Unlabeled Documents using EM (2000)Text Classification from Labe…Transductive Inference for Text Classification using Support Vector Machines (1999)Transductive Inference for Te…On the mathematical foundations of learning (2001)On the mathematical foundatio…Inductive learning algorithms and representations for text categorization (1998)Inductive learning algorithms…Semi-Supervised Classification with Graph Convolutional Networks (2016)Semi-Supervised Classificatio…A Comprehensive Survey on Transfer Learning (2020)A Comprehensive Survey on Tra…A survey of transfer learning (2016)A survey of transfer learningDeep Convolutional Neural Networks for Image Classification: A Comprehensive Review (2017)Deep Convolutional Neural Net…Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning (2018)Deeper Insights Into Graph Co…A survey on semi-supervised learning (2019)A survey on semi-supervised l…Introduction to Semi-Supervised Learning (2009)Introduction to Semi-Supervis…Trends in extreme learning machines: A review (2014)Trends in extreme learning ma…
16 of 16 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
Statistical Learning Theory199926,957
Combining labeled and unlabeled data with co-training19985,631
Semi-Supervised Learning20064,334
Learning with Local and Global Consistency20033,740
Text Classification from Labeled and Unlabeled Documents using EM20002,753
Transductive Inference for Text Classification using Support Vector Machines19992,721
On the mathematical foundations of learning20011,593
Inductive learning algorithms and representations for text categorization19981,469

What cites it, inside the corpus

PaperYearCited
Semi-Supervised Classification with Graph Convolutional Networks20168,058
A Comprehensive Survey on Transfer Learning20206,441
A survey of transfer learning20166,290
Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review20173,570
Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning20182,652
A survey on semi-supervised learning20192,636
Introduction to Semi-Supervised Learning20091,812
Trends in extreme learning machines: A review20141,752

Links

OpenAlex record

Topics

Machine Learning and AlgorithmsComputer Science
Face and Expression RecognitionComputer Science
Machine Learning and Data ClassificationComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports3 author record(s) attached.
  • supports50 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:47+00:00.

sha256 a08467ae9504f237…