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1
Better Document-Level Machine Translation with Bayes’ Rule
In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 346-360 (2020) (2020)
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2
A Hybrid MCDM Approach for Large Group Green Supplier Selection with Uncertain Linguistic Information ...
Quan, Mei-Yun; Ze-Ling Wang; Hu-Chen Liu. - : Zenodo, 2019
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3
A Hybrid MCDM Approach for Large Group Green Supplier Selection with Uncertain Linguistic Information ...
Quan, Mei-Yun; Ze-Ling Wang; Hu-Chen Liu. - : Zenodo, 2019
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4
Learning and Evaluating General Linguistic Intelligence ...
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5
Expanding Subjective Lexicons for Social Media Mining with Embedding Subspaces ...
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6
Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning ...
Tsvetkov, Yulia; Manaal Faruqui; Ling, Wang. - : Carnegie Mellon University, 2016
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7
Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning ...
Tsvetkov, Yulia; Manaal Faruqui; Ling, Wang. - : Carnegie Mellon University, 2016
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8
Learning to Compose Words into Sentences with Reinforcement Learning ...
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9
A linguistically motivated taxonomy for Machine Translation error analysis
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10
Recognition of Named-Event Passages in News Articles ...
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11
Wavelet-Based Analysis on the Complexity of Hydrologic Series Data under Multi-Temporal Scales
In: Entropy ; Volume 13 ; Issue 1 ; Pages 195-210 (2011)
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12
Entropy-Based Wavelet De-noising Method for Time Series Analysis
In: Entropy ; Volume 11 ; Issue 4 ; Pages 1123-1147 (2009)
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13
Mathematics and the sciences of the heavens and the earth. - Science and civilisation in China ; 3 : Mathematics and the sciences of the heavens and the earth. -
Needham, Joseph; Ling, Wang. - Cambridge : Cambridge University Press, 1972
MPI für Psycholinguistik
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14
Science and civilisation in China
Needham, Joseph; Ling, Wang. - Cambridge : University Press
MPI für Psycholinguistik
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15
Detecting Offensive Tweets via Topical Feature Discovery over a Large Scale Twitter Corpus
In: http://www.cs.cmu.edu/%7Eguangx/papers/cikm12.pdf
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16
RANKING FUZZY NUMBER BASED ON LEXICOGRAPHIC SCREENING PROCEDURE
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17
RANKING FUZZY NUMBER BASED ON LEXICOGRAPHIC SCREENING PROCEDURE
Abstract: Fuzzy numbers are used for representing the numerical quantities in a vague environment. Their ranking order has been an important issue for application purposes. Most of the existing ranking methods transform a fuzzy number into a real number based on certain criteria. There is yet no method that can always give a satisfactory solution. This study pointed out that it cannot be avoided for different fuzzy numbers to be corresponding to the same real number by any type of ranking functions. Therefore, sequential screening approach would be necessary for a complete order of fuzzy numbers. We summarize the properties for a sufficient and necessary set of ranking criteria. Then, based on the ranking order of these criteria, aLexicographical Screening Procedureis proposed, which has shown to be promising in ranking fuzzy number with efficient computation and ease of understanding. Six counterexamples of the existing methods were used for comparison. ; Fuzzy numbers, ranking criteria and properties, lexicographical screening procedure
URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622005001696
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18
Dialect, transaction cost and intra-national trade: evidence from China
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