[PDF] Top 20 Semi Supervised Representation Learning for Cross Lingual Text Classification
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Semi Supervised Representation Learning for Cross Lingual Text Classification
... for cross-lingual sentiment classification on the parallel training and test ...subspace representation learning method for cross- lingual text ... See full document
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A Robust Self Learning Framework for Cross Lingual Text Classification
... Semi-supervised Learning. There is a long his- tory of research on semi-supervised Learning to exploit unlabeled ...unsupervised cross-lingual word embed- ... See full document
5
Cross Lingual Sentiment Classification with Bilingual Document Representation Learning
... a semi-supervised manner by forcing the positive and negative documents to fall into different sides of a classification hyper- ...plane. Learning task-specific embedding has been proved to be ... See full document
10
Learning a Deep Hybrid Model for Semi Supervised Text Classification
... ist learning stem from the expressive power af- forded by models, such as the Deep Belief Net- work (DBN) (Hinton et ...stage learning process, where a generative archi- tecture is pre-trained and then used ... See full document
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Adaptive Semi supervised Learning for Cross domain Sentiment Classification
... correspondence learning (SCL), which uses pivot feature prediction to induce a projected fea- ture space that works well for both the source and the target ...Unsupervised representation learning ... See full document
10
Distributed Word Representation Learning for Cross Lingual Dependency Parsing
... different learning mechanisms (whether or not using labeled data) for induc- ing language-independent features, cross-lingual representation learning methods can be cate- gorized into ... See full document
11
Cross lingual Distillation for Text Classification
... on representation learning or the mapping of the in- duced representations in cross-language settings (Guo and Xiao, 2012b; Zhou et ...interlingua) representation for words or documents in ... See full document
11
Variational Pretraining for Semi supervised Text Classification
... to semi-supervised learning have been developed for NLP, including vari- ants of bootstrapping (Charniak, 1997; Blum and Mitchell, 1998; Zhou and Li, 2005; McClosky et ...and representation ... See full document
15
Analysis of Semi Supervised Learning Methods towards Multi Label Text Classification
... of semi supervised learning to improve classification accuracy of multi label text ...document representation such as latent semantic indexing may help in improving accuracy as ... See full document
6
Active Semi-supervised Framework with Data Editing
... active learning algorithms cannot be ...labeled text classification is transfer ...Transfer learning techniques can be used to improve sparsely labeled classification by transferring ... See full document
20
Cross lingual Discourse Relation Analysis: A corpus study and a semi supervised classification system
... our semi-supervised learning algorithm to recognize explicit discourse relations in Chinese, relying solely on discourse information available in ...multiway classification, our system ... See full document
11
Cross Language Text Classification by Model Translation and Semi Supervised Learning
... for cross-lingual classification of ...parallel text to build a subjectivity classifier for ...a cross-lingual projection of subjectivity labels, which are used to train ... See full document
11
Cross-lingual sentiment classification using semi-supervised learning
... Sentiment classification dates back to the early ...machine learning (or supervised) approach (Pang et ...2002). Supervised approaches rely on a large set of labelled data to train a ... See full document
53
Semi-Supervised Novelty Detection
... binary classification against the nominal data (this idea has been developed in more detail by Steinwart et ...NP classification on this modified ... See full document
37
A Semi Supervised Approach for Catchphrase Classification in Legal Text Documents
... the text, which can be removed without loss of relevant information for output and this, is done through the ...of text, and more than 30% of the ... See full document
11
A semi-supervised machine learning framework for microRNA classification
... Active learning is an iterative approach that begins by training a classifier using all available training ...active learning in miRNA classification ...tive learning has been applied to drug ... See full document
12
Semi Supervised Learning with Auxiliary Evaluation Component for Large Scale e Commerce Text Classification
... we significantly lacked high-quality labeled data for these problems. For example, the e-commerce product categorization dataset contains product ti- tles and 600 different categories for the product titles. This dataset ... See full document
9
Multi Label Text Classification through Label Propagation
... We evaluated our approach under a WEKA-based [23] framework running under Java JDK 1.6 with the libraries of MEKA and Mulan [21][22]. Jblas library for performing matrix operations while computing weights on graph edges. ... See full document
6
A Survey on Data Stream and Its Various Techniques
... a Semi-supervised classification algorithm for data ...online classification algorithms and a few known online semi-supervised algorithms, even for the situation with more than ... See full document
6
Multi modal curriculum learning for semi supervised image classification
... the learning process and generate encouraging classification ...higher classification due to its strong ability for handling difficult ...the classification correctness of the compared methods ... See full document
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