Fetching the paper…
Reading the bibliography…
In the covariate shift learning scenario, the training and test covariate distributions differ, so that a predictor's average loss over the training and test distributions also differ.
Sliced inverse regression for dimension reduction
Ker-Chau Li · 1991
Earlier work this paper cites.
Improving predictive inference under covariate shift by weighting the log-likelihood function
Hidetoshi Shimodaira · 2000
Earlier work this paper cites.
Sequential monte carlo methods in practice. series statistics for engineering and information science, 2001
Arnaud Doucet, Nando De Freitas, and NJ Gordon · 2001
Earlier work this paper cites.
Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data
Joseph DY Kang and Joseph L Schafer · 2007
Earlier work this paper cites.
Covariate shift adaptation by importance weighted cross validation
Masashi Sugiyama, Matthias Krauledat, and Klaus-Robert Muller · 2007
Earlier work this paper cites.
Efficient multiple hyperparameter learning for log-linear models
Chuan-sheng Foo, Chuong B Do, and Andrew Y Ng · 2008
Earlier work this paper cites.
Direct importance estimation with model selection and its application to covariate shift adaptation
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul V Buenau, and Motoaki Kawanabe · 2008
Earlier work this paper cites.
Discriminative learning under covariate shift
Steffen Bickel, Michael Brückner, and Tobias Scheffer · 2009
Earlier work this paper cites.
Extracting discriminative concepts for domain adaptation in text mining
Bo Chen, Wai Lam, Ivor Tsang, and Tak-Lam Wong · 2009
Earlier work this paper cites.
Covariate shift by kernel mean matching
Arthur Gretton, Alex Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, and Bernhard Schölkopf · 2009
Earlier work this paper cites.
A least-squares approach to direct importance estimation
Takafumi Kanamori, Shohei Hido, and Masashi Sugiyama · 2009
Earlier work this paper cites.
Learning bounds for importance weighting
Corinna Cortes, Yishay Mansour, and Mehryar Mohri · 2010
Cited alongside, same era.
Direct density ratio estimation with dimensionality reduction
Masashi Sugiyama, Satoshi Hara, Paul Von Bünau, Taiji Suzuki, Takafumi Kanamori, and Motoaki Kawanabe · 2010
Cited alongside, same era.
The Crisis on Campus
American Psychological Association · 2011
Cited alongside, same era.
An introduction to propensity score methods for reducing the effects of confounding in observational studies
Peter C Austin · 2011
Cited alongside, same era.
Relative density-ratio estimation for robust distribution comparison
Makoto Yamada, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, and Masashi Sugiyama · 2011
Cited alongside, same era.
National health and nutrition examination survey. analytic guidelines, 1999-2010
Clifford L Johnson, Ryne Paulose-Ram, Cynthia L Ogden, Margaret D Carroll, Deanna Kruszan-Moran, Sylvia M Dohrmann, and Lester R Curtin · 2013
Autograd: Reverse-mode differentiation of native python
Dougal Maclaurin, David Duvenaud, and Ryan P Adams · 2015
Later among the works it cites.
NHANES: Data from the US National Health and Nutrition Examination Study
Randall Pruim · 2015
Later among the works it cites.
Doubly robust covariate shift correction
Sashank Jakkam Reddi, Barnabas Poczos, and Alexander J Smola · 2015
Later among the works it cites.
Robust covariate shift regression
Xiangli Chen, Mathew Monfort, Anqi Liu, and Brian D Ziebart · 2016
Later among the works it cites.
Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
Later among the works it cites.
Robust supervised learning under uncertainty in dataset shift
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
UCI machine learning repository, 2013
M. Lichman · 2013
Cited alongside, same era.
Robust classification under sample selection bias
Anqi Liu and Brian Ziebart · 2014
Cited alongside, same era.
Robust learning under uncertain test distributions: Relating covariate shift to model misspecification
Junfeng Wen, Chun-nam Yu, and Russell Greiner · 2014
Cited alongside, same era.
Gradient-based hyperparameter optimization through reversible learning
Dougal Maclaurin, David Duvenaud, and Ryan Adams · 2015
Cited alongside, same era.
http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/
Libsvm datasets
Cited in the paper.
Weihua Hu, Issei Sato, and Masashi Sugiyama · 2016
Later among the works it cites.
Learning representations for counterfactual inference
Fredrik Johansson, Uri Shalit, and David Sontag · 2016
Later among the works it cites.
Pymanopt: A python toolbox for optimization on manifolds using automatic differentiation
James Townsend, Niklas Koep, and Sebastian Weichwald · 2016
Later among the works it cites.
Optnet: Differentiable optimization as a layer in neural networks
Brandon Amos and J Zico Kolter · 2017
Closest in time.
Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
Closest in time.