Invariant Risk Minimization

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Invariant Risk Minimization

5 July 2019

Martín Arjovsky

Ishaan Gulrajani

David Lopez-Paz

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Papers citing "Invariant Risk Minimization"

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Title
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers Divyat Mahajan Chenhao Tan Amit Sharma OOD CML 147 207 0 06 Dec 2019
Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations Sven Gowal Chongli Qin Po-Sen Huang taylan. cemgil Krishnamurthy Dvijotham Timothy A. Mann Pushmeet Kohli AAML OOD 74 57 0 06 Dec 2019
Observational Overfitting in Reinforcement Learning Xingyou Song Yiding Jiang Stephen Tu Yilun Du Behnam Neyshabur OffRL 124 140 0 06 Dec 2019
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 110 1,250 0 20 Nov 2019
Causality-based Feature Selection: Methods and Evaluations Kui Yu Xianjie Guo Lin Liu Jiuyong Li Hao Wang Zhaolong Ling Xindong Wu CML 90 97 0 17 Nov 2019
Generalizing to unseen domains via distribution matching Isabela Albuquerque João Monteiro Mohammad Javad Darvishi Bayazi T. Falk Ioannis Mitliagkas OOD 104 157 0 03 Nov 2019
Causal bootstrapping Max A. Little Reham Badawy CML 56 20 0 21 Oct 2019
Predicting with High Correlation Features Devansh Arpit Caiming Xiong R. Socher OODD OOD 58 7 0 01 Oct 2019
Alleviating Privacy Attacks via Causal Learning Shruti Tople Amit Sharma A. Nori MIACV OOD 98 32 0 27 Sep 2019
Learning Invariants through Soft Unification Nuri Cingillioglu A. Russo NAI 31 2 0 16 Sep 2019
Modular Meta-Learning with Shrinkage Yutian Chen A. Friesen Feryal M. P. Behbahani Arnaud Doucet David Budden Matthew W. Hoffman Nando de Freitas KELM OffRL 112 35 0 12 Sep 2019
Population-aware Hierarchical Bayesian Domain Adaptation via Multiple-component Invariant Learning Vishwali Mhasawade N. Rehman R. Chunara OOD 70 9 0 24 Aug 2019
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions Matthew Faw Rajat Sen Karthikeyan Shanmugam Constantine Caramanis Sanjay Shakkottai 63 3 0 23 Jul 2019
A Unifying Causal Framework for Analyzing Dataset Shift-stable Learning Algorithms Adarsh Subbaswamy Bryant Chen Suchi Saria OOD 57 18 0 27 May 2019
A Survey of Learning Causality with Data: Problems and Methods Ruocheng Guo Lu Cheng Jundong Li P. R. Hahn Huan Liu CML 74 168 0 25 Sep 2018