The Experts below are selected from a list of 1584 Experts worldwide ranked by ideXlab platform
Iryna Gurevych - One of the best experts on this subject based on the ideXlab platform.
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still not there comparing traditional Sequence to Sequence models to encoder decoder neural networks on Monotone string translation tasks
International Conference on Computational Linguistics, 2016Co-Authors: Carsten Schnober, Steffen Eger, Eriklân Do Dinh, Iryna GurevychAbstract:We analyze the performance of encoder-decoder neural models and compare them with well-known established methods. The latter represent different classes of traditional approaches that are applied to the Monotone Sequence-to-Sequence tasks OCR post-correction, spelling correction, grapheme-to-phoneme conversion, and lemmatization. Such tasks are of practical relevance for various higher-level research fields including \textit{digital humanities}, automatic text correction, and speech recognition. We investigate how well generic deep-learning approaches adapt to these tasks, and how they perform in comparison with established and more specialized methods, including our own adaptation of pruned CRFs.
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still not there comparing traditional Sequence to Sequence models to encoder decoder neural networks on Monotone string translation tasks
arXiv: Computation and Language, 2016Co-Authors: Carsten Schnober, Steffen Eger, Eriklân Do Dinh, Iryna GurevychAbstract:We analyze the performance of encoder-decoder neural models and compare them with well-known established methods. The latter represent different classes of traditional approaches that are applied to the Monotone Sequence-to-Sequence tasks OCR post-correction, spelling correction, grapheme-to-phoneme conversion, and lemmatization. Such tasks are of practical relevance for various higher-level research fields including digital humanities, automatic text correction, and speech recognition. We investigate how well generic deep-learning approaches adapt to these tasks, and how they perform in comparison with established and more specialized methods, including our own adaptation of pruned CRFs.
Rudi Wietsma - One of the best experts on this subject based on the ideXlab platform.
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Monotone convergence theorems for semi-bounded operators and forms with applications
Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, 2010Co-Authors: Jussi Behrndt, Seppo Hassi, Henk De Snoo, Rudi WietsmaAbstract:Let Hn be a Monotone Sequence of non-negative self-adjoint operators or relations in a Hilbert space. Then there exists a self-adjoint relation H∞ such that Hn converges to H∞ in the strong resolvent sense. This result and related limit results are explored in detail and new simple proofs are presented. The corresponding statements for Monotone Sequences of semi-bounded closed forms are established as immediate conSequences. Applications and examples, illustrating the general results, include Sequences of multiplication operators, Sturm–Liouville operators with increasing � ∞ � ∞ �
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Monotone convergence theorems for semi-bounded operators and forms with applications
Proceedings of the Royal Society of Edinburgh: Section A Mathematics, 2010Co-Authors: Jussi Behrndt, Seppo Hassi, Henk De Snoo, Rudi WietsmaAbstract:AbstractLet Hn be a Monotone Sequence of non-negative self-adjoint operators or relations in a Hilbert space. Then there exists a self-adjoint relation H∞ such that Hn converges to H∞ in the strong resolvent sense. This result and related limit results are explored in detail and new simple proofs are presented. The corresponding statements for Monotone Sequences of semi-bounded closed forms are established as immediate conSequences. Applications and examples, illustrating the general results, include Sequences of multiplication operators, Sturm–Liouville operators with increasing potentials, forms associated with Kreĭn–Feller differential operators, singular perturbations of non-negative self-adjoint operators and the characterization of the Friedrichs and Kreĭn–von Neumann extensions of a non-negative operator or relation.
Carsten Schnober - One of the best experts on this subject based on the ideXlab platform.
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still not there comparing traditional Sequence to Sequence models to encoder decoder neural networks on Monotone string translation tasks
International Conference on Computational Linguistics, 2016Co-Authors: Carsten Schnober, Steffen Eger, Eriklân Do Dinh, Iryna GurevychAbstract:We analyze the performance of encoder-decoder neural models and compare them with well-known established methods. The latter represent different classes of traditional approaches that are applied to the Monotone Sequence-to-Sequence tasks OCR post-correction, spelling correction, grapheme-to-phoneme conversion, and lemmatization. Such tasks are of practical relevance for various higher-level research fields including \textit{digital humanities}, automatic text correction, and speech recognition. We investigate how well generic deep-learning approaches adapt to these tasks, and how they perform in comparison with established and more specialized methods, including our own adaptation of pruned CRFs.
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still not there comparing traditional Sequence to Sequence models to encoder decoder neural networks on Monotone string translation tasks
arXiv: Computation and Language, 2016Co-Authors: Carsten Schnober, Steffen Eger, Eriklân Do Dinh, Iryna GurevychAbstract:We analyze the performance of encoder-decoder neural models and compare them with well-known established methods. The latter represent different classes of traditional approaches that are applied to the Monotone Sequence-to-Sequence tasks OCR post-correction, spelling correction, grapheme-to-phoneme conversion, and lemmatization. Such tasks are of practical relevance for various higher-level research fields including digital humanities, automatic text correction, and speech recognition. We investigate how well generic deep-learning approaches adapt to these tasks, and how they perform in comparison with established and more specialized methods, including our own adaptation of pruned CRFs.
Jussi Behrndt - One of the best experts on this subject based on the ideXlab platform.
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Monotone convergence theorems for semi-bounded operators and forms with applications
Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, 2010Co-Authors: Jussi Behrndt, Seppo Hassi, Henk De Snoo, Rudi WietsmaAbstract:Let Hn be a Monotone Sequence of non-negative self-adjoint operators or relations in a Hilbert space. Then there exists a self-adjoint relation H∞ such that Hn converges to H∞ in the strong resolvent sense. This result and related limit results are explored in detail and new simple proofs are presented. The corresponding statements for Monotone Sequences of semi-bounded closed forms are established as immediate conSequences. Applications and examples, illustrating the general results, include Sequences of multiplication operators, Sturm–Liouville operators with increasing � ∞ � ∞ �
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Monotone convergence theorems for semi-bounded operators and forms with applications
Proceedings of the Royal Society of Edinburgh: Section A Mathematics, 2010Co-Authors: Jussi Behrndt, Seppo Hassi, Henk De Snoo, Rudi WietsmaAbstract:AbstractLet Hn be a Monotone Sequence of non-negative self-adjoint operators or relations in a Hilbert space. Then there exists a self-adjoint relation H∞ such that Hn converges to H∞ in the strong resolvent sense. This result and related limit results are explored in detail and new simple proofs are presented. The corresponding statements for Monotone Sequences of semi-bounded closed forms are established as immediate conSequences. Applications and examples, illustrating the general results, include Sequences of multiplication operators, Sturm–Liouville operators with increasing potentials, forms associated with Kreĭn–Feller differential operators, singular perturbations of non-negative self-adjoint operators and the characterization of the Friedrichs and Kreĭn–von Neumann extensions of a non-negative operator or relation.
Steffen Eger - One of the best experts on this subject based on the ideXlab platform.
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still not there comparing traditional Sequence to Sequence models to encoder decoder neural networks on Monotone string translation tasks
International Conference on Computational Linguistics, 2016Co-Authors: Carsten Schnober, Steffen Eger, Eriklân Do Dinh, Iryna GurevychAbstract:We analyze the performance of encoder-decoder neural models and compare them with well-known established methods. The latter represent different classes of traditional approaches that are applied to the Monotone Sequence-to-Sequence tasks OCR post-correction, spelling correction, grapheme-to-phoneme conversion, and lemmatization. Such tasks are of practical relevance for various higher-level research fields including \textit{digital humanities}, automatic text correction, and speech recognition. We investigate how well generic deep-learning approaches adapt to these tasks, and how they perform in comparison with established and more specialized methods, including our own adaptation of pruned CRFs.
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still not there comparing traditional Sequence to Sequence models to encoder decoder neural networks on Monotone string translation tasks
arXiv: Computation and Language, 2016Co-Authors: Carsten Schnober, Steffen Eger, Eriklân Do Dinh, Iryna GurevychAbstract:We analyze the performance of encoder-decoder neural models and compare them with well-known established methods. The latter represent different classes of traditional approaches that are applied to the Monotone Sequence-to-Sequence tasks OCR post-correction, spelling correction, grapheme-to-phoneme conversion, and lemmatization. Such tasks are of practical relevance for various higher-level research fields including digital humanities, automatic text correction, and speech recognition. We investigate how well generic deep-learning approaches adapt to these tasks, and how they perform in comparison with established and more specialized methods, including our own adaptation of pruned CRFs.