Minimax and Neyman–Pearson Meta-Learning for Outlier Languages
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Anders Sogaard | Siva Reddy | Rahul Aralikatte | Edoardo Maria Ponti | Disha Shrivastava | Siva Reddy | Anders Søgaard | E. Ponti | Disha Shrivastava | Rahul Aralikatte
[1] Florian Schäfer,et al. Competitive Gradient Descent , 2019, NeurIPS.
[2] Sridhar Mahadevan,et al. Global Convergence to the Equilibrium of GANs using Variational Inequalities , 2018, ArXiv.
[3] Jian Zhang,et al. SQuAD: 100,000+ Questions for Machine Comprehension of Text , 2016, EMNLP.
[4] A. McCallum,et al. Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks , 2019, COLING.
[5] Yoshua Bengio,et al. Bayesian Model-Agnostic Meta-Learning , 2018, NeurIPS.
[6] Jörg Tiedemann,et al. Cross-Lingual Dependency Parsing with Universal Dependencies and Predicted PoS Labels , 2015, DepLing.
[7] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[8] Emily M. Bender. Linguistically Naïve != Language Independent: Why NLP Needs Linguistic Typology , 2009 .
[9] Thierry Poibeau,et al. Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing , 2018, Computational Linguistics.
[10] Kjell A. Doksum,et al. Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition , 2015 .
[11] Graham Neubig,et al. Balancing Training for Multilingual Neural Machine Translation , 2020, ACL.
[12] Rich Caruana,et al. Multitask Learning , 1998, Encyclopedia of Machine Learning and Data Mining.
[13] Lorien Y. Pratt,et al. Discriminability-Based Transfer between Neural Networks , 1992, NIPS.
[14] Marc Teboulle,et al. Mirror descent and nonlinear projected subgradient methods for convex optimization , 2003, Oper. Res. Lett..
[15] Sebastian Ruder,et al. Neural transfer learning for natural language processing , 2019 .
[16] Sergey Levine,et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks , 2017, ICML.
[17] Anna Korhonen,et al. On the Relation between Linguistic Typology and (Limitations of) Multilingual Language Modeling , 2018, EMNLP.
[18] Guoxin Wang,et al. Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal Resources , 2019, AAAI.
[19] Xin Zhang,et al. Worst-Case-Aware Curriculum Learning for Zero and Few Shot Transfer , 2020, ArXiv.
[20] Slav Petrov,et al. Unsupervised Part-of-Speech Tagging with Bilingual Graph-Based Projections , 2011, ACL.
[21] Thomas L. Griffiths,et al. Recasting Gradient-Based Meta-Learning as Hierarchical Bayes , 2018, ICLR.
[22] Qianchu Liu,et al. XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning , 2020, EMNLP.
[23] Eunsol Choi,et al. TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages , 2020, Transactions of the Association for Computational Linguistics.
[24] S. Zabell. Symmetry and its discontents : essays on the history of inductive probability , 2005 .
[25] Mark Dredze,et al. Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT , 2019, EMNLP.
[26] Thore Graepel,et al. The Mechanics of n-Player Differentiable Games , 2018, ICML.
[27] Barak A. Pearlmutter. Fast Exact Multiplication by the Hessian , 1994, Neural Computation.
[28] Sebastian Ruder,et al. A survey of cross-lingual embedding models , 2017, ArXiv.
[29] Ryan Cotterell,et al. Towards Zero-shot Language Modeling , 2019, EMNLP.
[30] Sébastien M. R. Arnold,et al. learn2learn: A Library for Meta-Learning Research , 2020, ArXiv.
[31] Ryan Cotterell,et al. Probabilistic Typology: Deep Generative Models of Vowel Inventories , 2017, ACL.
[32] Sergey Levine,et al. Probabilistic Model-Agnostic Meta-Learning , 2018, NeurIPS.
[33] Amir Globerson,et al. Nightmare at test time: robust learning by feature deletion , 2006, ICML.
[34] Ryan Cotterell,et al. Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages , 2021, Transactions of the Association for Computational Linguistics.
[35] G. Lock. The State and I , 1981 .
[36] Aryan Mokhtari,et al. Task-Robust Model-Agnostic Meta-Learning , 2020, NeurIPS.
[37] Anna Korhonen,et al. Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction , 2018, TACL.