Timezone: »
Adapting to Shifts in Latent Confounders via Observed Concepts and Proxies
Matt Kusner · Ibrahim Alabdulmohsin · Stephen Pfohl · Olawale Salaudeen · Arthur Gretton · Sanmi Koyejo · Jessica Schrouff · Alexander D'Amour
We address the problem of unsupervised domain adaptation when the source differs from the target because of a shift in the distribution of a latent confounder. In this case, neither covariate shift nor label shift assumptions apply. When all data is discrete, we show that the optimal target predictor can be non-parametrically identified with the help of concept and proxy variables, available only in the source, and unlabeled data from the target.
Author Information
Matt Kusner (University College London)
Ibrahim Alabdulmohsin (Google Research)
Stephen Pfohl (Google)
Olawale Salaudeen (Google)
Arthur Gretton (Gatsby Computational Neuroscience Unit)
Sanmi Koyejo (Google / Illinois)
Jessica Schrouff (Google Health)
Alexander D'Amour (Google Brain)
More from the Same Authors
-
2022 : Fairness and robustness in anti-causal prediction »
Maggie Makar · Alexander D'Amour -
2022 : Evaluating Self-Supervised Learned Molecular Graphs »
Hanchen Wang · Shengchao Liu · Jean Kaddour · Qi Liu · Jian Tang · Matt Kusner · Joan Lasenby -
2022 : Fairness and robustness in anti-causal prediction »
Maggie Makar · Alexander D'Amour -
2022 : Evaluating Self-Supervised Learned Molecular Graphs »
Hanchen Wang · Hanchen Wang · Shengchao Liu · Shengchao Liu · Jean Kaddour · Jean Kaddour · Qi Liu · Qi Liu · Jian Tang · Jian Tang · Matt Kusner · Matt Kusner · Joan Lasenby · Joan Lasenby -
2022 Poster: Importance Weighted Kernel Bayes' Rule »
Liyuan Xu · Yutian Chen · Arnaud Doucet · Arthur Gretton -
2022 Spotlight: Importance Weighted Kernel Bayes' Rule »
Liyuan Xu · Yutian Chen · Arnaud Doucet · Arthur Gretton -
2021 Workshop: The Neglected Assumptions In Causal Inference »
Niki Kilbertus · Lily Hu · Laura Balzer · Uri Shalit · Alexander D'Amour · Razieh Nabi -
2021 Poster: Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction »
Afsaneh Mastouri · Yuchen Zhu · Limor Gultchin · Anna Korba · Ricardo Silva · Matt J. Kusner · Arthur Gretton · Krikamol Muandet -
2021 Spotlight: Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction »
Afsaneh Mastouri · Yuchen Zhu · Limor Gultchin · Anna Korba · Ricardo Silva · Matt J. Kusner · Arthur Gretton · Krikamol Muandet -
2020 Poster: Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data »
Tamara Fernandez · Arthur Gretton · Nicolas Rivera · Wenkai Xu -
2020 Poster: Learning Deep Kernels for Non-Parametric Two-Sample Tests »
Feng Liu · Wenkai Xu · Jie Lu · Guangquan Zhang · Arthur Gretton · D.J. Sutherland -
2019 : Invited Talk - Arthur Gretton: Relative goodness-of-fit tests for models with latent variables. »
Arthur Gretton -
2019 Poster: Learning deep kernels for exponential family densities »
Li Kevin Wenliang · D.J. Sutherland · Heiko Strathmann · Arthur Gretton -
2019 Oral: Learning deep kernels for exponential family densities »
Li Kevin Wenliang · D.J. Sutherland · Heiko Strathmann · Arthur Gretton -
2017 Poster: An Adaptive Test of Independence with Analytic Kernel Embeddings »
Wittawat Jitkrittum · Zoltan Szabo · Arthur Gretton -
2017 Talk: An Adaptive Test of Independence with Analytic Kernel Embeddings »
Wittawat Jitkrittum · Zoltan Szabo · Arthur Gretton