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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 16 of 16 1 Conditional Poisson Stochastic Beams ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Amini, Afra; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 2 Higher-order Derivatives of Weighted Finite-state Machines ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Cotterell, Ryan; Vieira, Tim. - : Underline Science Inc., 2021 BASE Show details 3 On Finding the K-best Non-projective Dependency Trees ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Cotterell, Ryan; Vieira, Tim. - : Underline Science Inc., 2021 BASE Show details 4 Searching for More Efficient Dynamic Programs ... Vieira, Tim; Cotterell, Ryan; Eisner, Jason. - : ETH Zurich, 2021 BASE Show details 5 On Finding the K-best Non-projective Dependency Trees ... Zmigrod, Ran; Vieira, Tim; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details 6 Efficient computation of expectations under spanning tree distributions ... Zmigrod, Ran; Vieira, Tim; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details 7 Higher-order Derivatives of Weighted Finite-state Machines ... Zmigrod, Ran; Vieira, Tim; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details 8 On Finding the K-best Non-projective Dependency Trees Zmigrod, Ran; Cotterell, Ryan; Vieira, Tim In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (2021) BASE Show details 9 Higher-order Derivatives of Weighted Finite-state Machines Zmigrod, Ran; Cotterell, Ryan; Vieira, Tim In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (2021) Abstract: Weighted finite-state machines are a fundamental building block of NLP systems. They have withstood the test of time-from their early use in noisy channel models in the 1990s up to modern-day neurally parameterized conditional random fields. This work examines the computation of higher-order derivatives with respect to the normalization constant for weighted finite-state machines. We provide a general algorithm for evaluating derivatives of all orders, which has not been previously described in the literature. In the case of second-order derivatives, our scheme runs in the optimal O(A(2) N-4) time where A is the alphabet size and N is the number of states. Our algorithm is significantly faster than prior algorithms. Additionally, our approach leads to a significantly faster algorithm for computing second-order expectations, such as covariance matrices and gradients of first-order expectations. URL: https://hdl.handle.net/20.500.11850/507678 https://doi.org/10.3929/ethz-b-000507678 BASE Hide details 10 Efficient computation of expectations under spanning tree distributions Cotterell, Ryan; Zmigrod, Ran; Vieira, Tim In: Transactions of the Association for Computational Linguistics, 9 (2021) BASE Show details 11 Efficient Sampling of Dependency Structure Vieira, Tim; Zmigrod, Ran; Cotterell, Ryan In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021) BASE Show details 12 Searching for More Efficient Dynamic Programs Cotterell, Ryan; Eisner, Jason; Vieira, Tim In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021) BASE Show details 13 Please Mind the Root: Decoding Arborescences for Dependency Parsing Vieira, Tim; Cotterell, Ryan; Zmigrod, Ran In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020) BASE Show details 14 If beam search is the answer, what was the question? Meister, Clara; Cotterell, Ryan; Vieira, Tim In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020) BASE Show details 15 A Joint Model of Orthography and Morphological Segmentation Cotterell, Ryan; Vieira, Tim; Schütze, Hinrich. - : Association for Computational Linguistics, 2016. : Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016 BASE Show details 16 Grammarless parsing for joint inference Naradowsky, Jason; Vieira, Tim; Smith, David A. - : Mumbai, India : The COLING 2012 Organizing Committee, 2012 BASE Show details

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