Towards a general independent subspace analysis

By Fabian J Theis. 2006

115 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Molecular Biology, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Kenji Fukumizu
2. Bernhard Schölkopf
3. Arthur Gretton
4. Le Song
5. Michel Besserve
6. Luigi Gresele
7. Wieland Brendel
8. Alex Smola

In Molecular Biology

1. Bernhard Schölkopf
2. Arthur Gretton
3. Alex Smola
4. Le Song
5. Kenji Fukumizu
6. Michel Besserve
7. Francesco Locatello
8. Wieland Brendel

In Signal Processing

1. Bernhard Schölkopf
2. Kenji Fukumizu
3. Arthur Gretton
4. Le Song
5. Alex Smola
6. Francesco Locatello
7. Michel Besserve
8. Wieland Brendel

Citations in the corpus

• RGB-D-based Human Motion Recognition with Deep Learning: A Survey (2017, background): “(2011) presented an extension of the independent subspace analysis algorithm (Theis, 2007) to learn invariant spatio-temporal features from unlabeled video data.”
• Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style (2021, background): “1 is related to independent subspace analysis [16, 53, 73, 114], which also aims to identify blocks of random variables as opposed to individual factors, though under an independence assumption across blocks, and typically not within a multi-view setting as studied in the present work.”
• A Kernel Statistical Test of Independence (2007, background): “Finally, in Section 4, we give our experimental results, both for testin g dependence between random vectors (which could be used for instance to verify convergence in in dependent subspace analysis [25]), and for testing dependence between text and its translation .”