Who Supported Obama in 2012?: Ecological Inference through Distribution Regression
By Seth R. Flaxman, Yu-Xiang Wang, Alex Smola. 2015
62 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Control and Systems Engineering, Statistics and Probability, Social Sciences & Humanities
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Bernhard Schölkopf
- Bharath K. Sriperumbudur
- Arthur Gretton
- Krikamol Muandet
- Kenji Fukumizu
- Barnab'as P'oczos
- David Lopez-Paz
- Dino Sejdinovic
In Control and Systems Engineering
- Arthur Gretton
- Bernhard Schölkopf
- Kenji Fukumizu
- Bharath K. Sriperumbudur
- Krikamol Muandet
- Zoltán Szabó
- Barnab'as P'oczos
- Dino Sejdinovic
In Statistics and Probability
- Arthur Gretton
- Bharath K. Sriperumbudur
- Kenji Fukumizu
- Bernhard Schölkopf
- Krikamol Muandet
- Dino Sejdinovic
- Barnab'as P'oczos
- Zoltán Szabó
In Social Sciences & Humanities
Citations in the corpus
- Kernel Mean Embedding of Distributions: A Review and Beyonds (2016, methodology): “In a similar vein, Flaxman et al. (2015a) adopts Gaussian process regression in conditional independence test on non-i.i.d. observations.”
- Learning Theory for Distribution Regression (2014, background): “, 2012) or ecological inference (Flaxman et al., 2015); for a recent review on multi-output prediction methods see (Álvarez et al.”
- Proposal : Scalable , Active and Flexible Learning on Distributions (2015, unknown): “This natural approximation, or its equivalents, have been consideredmany times quite recently (Mehta and Gray 2010; Li and Tsang 2011; Zhao and Meng 2014; Chwialkowski et al. 2015; Flaxman et al. 2015; Jitkrittum et al. 2015; Lopez-Paz et al. 2015; Sutherland, J. B. Oliva, et al. 2015; Sutherland an”