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AANG: Automating Auxiliary Learning



Lucio M. Dery , Paul Michel , Mikhail Khodak , Graham Neubig , Ameet Talwalkar

* 18 pages, 9 tables and 4 figures 

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Distributionally Robust Models with Parametric Likelihood Ratios



Paul Michel , Tatsunori Hashimoto , Graham Neubig

* ICLR 2022 

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Balancing Average and Worst-case Accuracy in Multitask Learning



Paul Michel , Sebastian Ruder , Dani Yogatama

* Under review 

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Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative



Lucio M. Dery , Paul Michel , Ameet Talwalkar , Graham Neubig

* 16 pages, 4 figures 

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Learning Neural Models for Natural Language Processing in the Face of Distributional Shift



Paul Michel

* PhD thesis 

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Examining and Combating Spurious Features under Distribution Shift



Chunting Zhou , Xuezhe Ma , Paul Michel , Graham Neubig

* Accepted by ICML2021 

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Modeling the Second Player in Distributionally Robust Optimization



Paul Michel , Tatsunori Hashimoto , Graham Neubig

* Accepted at ICLR 2021 

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Weight Poisoning Attacks on Pre-trained Models



Keita Kurita , Paul Michel , Graham Neubig

* Published as a long paper at ACL 2020 

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Optimizing Data Usage via Differentiable Rewards



Xinyi Wang , Hieu Pham , Paul Michel , Antonios Anastasopoulos , Graham Neubig , Jaime Carbonell


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