Learning When the Concept Shifts: Confounding, Invariance, and Dimension
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Learning When the Concept Shifts: Confounding, Invariance, and Dimension Reduction

22 June 2024

Kulunu Dharmakeerthi

Tengyuan Liang

Papers citing "Learning When the Concept Shifts: Confounding, Invariance, and Dimension Reduction"

8 / 8 papers shown

Title
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria Tengyuan Liang 54 1 0 05 Dec 2022
Marginal Singularity, and the Benefits of Labels in Covariate-Shift Samory Kpotufe Guillaume Martinet 110 95 0 05 Mar 2018
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation James Townsend Niklas Koep S. Weichwald 70 247 0 10 Mar 2016
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 366 9,467 0 28 May 2015
Learning Transferable Features with Deep Adaptation Networks Mingsheng Long Yue Cao Jianmin Wang Michael I. Jordan OOD 215 5,189 0 10 Feb 2015
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 114 966 0 06 Jan 2015
Deep Domain Confusion: Maximizing for Domain Invariance Eric Tzeng Judy Hoffman Ning Zhang Kate Saenko Trevor Darrell OOD 165 2,598 0 10 Dec 2014
On Causal and Anticausal Learning Bernhard Schölkopf Dominik Janzing J. Peters Eleni Sgouritsa Kun Zhang Joris Mooij CML 81 607 0 27 Jun 2012

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