instance-weighting
Instance Weighting for Domain Adaptation in NLP
... In general, the domain adaptation problem arises when the source instances and the target instances are from two different, but related distributions. We formally analyze and characterize the domain adaptation problem ...
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Discriminative Instance Weighting for Domain Adaptation in Statistical Machine Translation
... There is a fairly large body of work on SMT adaptation. We introduce several new ideas. First, we aim to explicitly characterize examples from OUT as belonging to general language or not. Pre- vious approaches have tried ...
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Sentence Level Instance Weighting for Graph Based and Transition Based Dependency Parsing
... In dependency parsing, domain adaptation re- ceived attention in the CoNLL 2007 Shared Task. While semi-supervised learning and structural cor- respondence learning were used by participants in the CoNLL 2007 Shared ...
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Not All Dialogues are Created Equal: Instance Weighting for Neural Conversational Models
... The limitations of neural conversational models trained on large, noisy dialogue corpora such as movie and TV subtitles have been discussed in several papers. Some of the issues raised in pre- vious papers are the ...
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Better Fine-Tuning via Instance Weighting for Text Classification
... an Instance Weighting based Fine- tuning (IW-Fit) method, which revises the fine-tuning stage to improve the final performance on the target ...adjusts instance weights at each fine-tuning epoch ...
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Instance Weighting for Neural Machine Translation Domain Adaptation
... iii) Instance Weighting. Instance Weighting has been applied to several NLP domain adaptation tasks (Jiang and Zhai, 2007), such as POS tagging, entity type classification and especially PBSMT ...
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Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
... Towards Compact and Fast Neural Machine Translation Using a Combined Method Xiaowei Zhang, Wei Chen, Feng Wang, Shuang Xu and Bo Xu.. Instance Weighting for Neural Machine Translation Do[r] ...
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Domain Adaptation with Active Learning for Coreference Resolution
... main instance weighting for coreference ...domain instance weighting achieves performance on MEDLINE ab- stracts similar to a system trained on coref- erence annotation of only target domain ...
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A Distributed Clustering Approach for Heterogeneous Environments Using Fuzzy Rough Set Theory
... Suppose that there are r sites which each one has access to a subset of features. In the first step, instances are partitioned with any clustering algorithm in each node and then all instances in the same cluster take ...
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Data point selection for cross language adaptation of dependency parsers
... of instance weighting, similar to what is often used for correcting sample selection bias or for domain adaptation, to improve the approach in Ze- man and Resnik (2008) by selecting only sentences in the ...
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Instance Sampling for Multilingual Coreference Resolution
... All distinct methods for instance sampling were employed in different CR systems. Some of them were completely ML based, others used a hybrid approach to the task. Moreover, none of the sys- tems was able to test ...
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Learning Instance-Specific Predictive Models
... An instance-specific version of logistic regression could, for example, select different variables for different instances being predicted, compared to the standard population-wide version that selects a single ...
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A Repository of Frame Instance Lexicalizations for Generation
... the instance lex- icalization by applying the composition method of Basile and Bos ...incorrect instance lex- icalizations, usually containing variables instead of being complete surface ...For ...
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Instance search retrospective with focus on TRECVID
... Initial attempts of the application of DCNN to image retrieval were, however, unsuccessful. Babenko et al. [5] report one of the first attempts to use DCNN responses as holistic features of images but the performance is ...
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Multiple-Instance Learning from Distributions
... We could make SIL more closely resemble our generative model by randomly discarding all but one instance in every bag. However, this would dramatically reduce the size of most practical MI data sets and would ...
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Using skewness to estimate the semi strong GARCH(1,1) model
... optimal weighting matrix is robust to the biases caused by many (potentially weak) instruments, as is the jackknife GMM estimator ...optimal weighting matrix is unavailable out of a concern over the ...
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Instance Based Acquisition of Vowel Harmony
... Fixed-rate representations For the simulations described here, I use fixed-rate trajectories, in which consonants and vowels are represented in a temporally coarse-grained manner with sin- gle (F 1, F 2) tuples. ...
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PLIERS at VLC2
... The queries are based on topics 351 to 400 of the TREC-7 ad-hoc track: 50 queries in all. The terms were extracted from TREC-7 topic descriptions using an Okapi query generator utility and put through the Lovins stemmer ...
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Mathematical Method for Selecting Team Members from a Social Network
... may be the most important view because in this case the instrumental social network data includes both work- and assistance-level factors. Pure friendship data gives some extra information. In a military context the ...
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10.1.1.731.3119.pdf
... All students at the selected schools were asked to take part in IS1. Approximately 200 students from each selected school were asked to complete IH1 and nearly all respondents to IH1 were approached for IH2. The implicit ...
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