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

2006 · Journal of Machine Learning Research · 2,132 citations · 3 from inside this corpus

BelkinMikhail low, NiyogiPartha low, SindhwaniVikas 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.

3 of 3 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 cites it, inside the corpus

Paper	Year	Cited
A Comprehensive Survey on Transfer Learning	2020	6,441
Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning	2018	2,652
Trends in extreme learning machines: A review	2014	1,752

Links

DOI · OpenAlex record

Topics

Machine Learning and Data Classification

Computer Science

Is this record sound?

partial

One field of this record is missing or disagrees with another. What is shown below is what the source publishes.

supports3 author record(s) attached.
weakensNo references are recorded despite 2,132 citations. A paper this heavily cited did not cite nothing, so the record is incomplete.
neutralThe DOI carries no year to check against.
supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:51+00:00.

sha256 6e314d9c6052d1ed…