[PDF] Top 20 Semi Supervised Learning for Neural Keyphrase Generation
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Semi Supervised Learning for Neural Keyphrase Generation
... 3, semi- supervised learning significantly improves the ab- sent generation performance, compared to the baseline ...task learning method is more effective at gen- erating absent ... See full document
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Shrinking Japanese Morphological Analyzers With Neural Networks and Semi supervised Learning
... How much data do we need? For our main ex- periments, we train all models for a single epoch on our silver dataset. Figure 4 shows KU train (our dev set) Seg F1 curves for L:B and S:B for three epochs. We ran each ... See full document
12
Strong Baselines for Neural Semi Supervised Learning under Domain Shift
... un- supervised approach; the less lexicalized and more context-driven approach taken by FLORS is clearly superior for these cases, resulting in higher UWT accuracies for 4/5 ... See full document
11
Morpho syntactic Lexicon Generation Using Graph based Semi supervised Learning
... Lexicon generation. Eskander et al. (2013) con- struct morpho-syntactic lexicons by incrementally merging inflectional classes with shared morpholog- ical features. Natural language lexicons have often been ... See full document
16
Three phase training to address data sparsity in Neural Machine Translation
... contemporary neural machine transla- tion (NMT) techniques, especially for resource-scarce language ...weakly supervised and semi- supervised learning with NMT tech- niques to build a ... See full document
10
Topic Aware Neural Keyphrase Generation for Social Media Language
... NTM, stop words and punctuation were removed. Parameter Settings. We implement our model based on the pytorch framework in Paszke et al. (2017). For NTM, we implement it following the design 10 in Zeng et al. (2018) and ... See full document
11
Semi Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models
... a learning scheme which provides the ability to jointly learn two mod- els for NLG and for NLU using large amount of unannotated data and small amount of anno- tated ... See full document
11
Paraphrase Generation for Semi Supervised Learning in NLU
... that neural machine transla- tion (NMT) systems perform better than phrase- based MT systems in paraphrase generation ...phrase generation using the transformer leads to better performance compared ... See full document
10
Semi Supervised Learning for Neural Machine Translation
... end-to-end neural machine transla- tion (NMT) has made remarkable progress recently, NMT systems only rely on par- allel corpora for parameter ...a semi- supervised approach for training NMT models ... See full document
10
Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewards
... reinforcement learning (RL) approach for keyphrase generation, with an adaptive reward function that encourages a model to generate both sufficient and accu- rate ... See full document
12
Unbiased Generative Semi-Supervised Learning
... ML semi-supervised learning, as well as the desire to utilise unlabelled samples in non-generative models, a large number of alternative objective functions have been proposed to take advantage of ... See full document
77
Semi-Supervised Learning with Measure Propagation
... Text classification involves automatically assigning a given document to a fixed number of semantic categories. Each document may belong to one, many, or none of the categories. In general, text clas- sification is a ... See full document
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Keyphrase Extraction in Scientific Articles: A Supervised Approach
... Keyphrase is a word or set of words that describe the close relationship of content and context in the document. Keyphrases are sometimes simple nouns or noun phrases (NPs) that represent the key ideas of the ... See full document
8
Large Margin Semi-supervised Learning
... classification, semi-supervised learning occurs when a large amount of unlabeled data is avail- able with only a small number of labeled ...margin semi-supervised learning ... See full document
25
Towards Automated Semi-Supervised Learning
... Meta-learning is good at suggesting some instantiations of the SSL techniques which are likely to perform well in a quick manner, whereas it could not provide fine-grained per- formance. In contrast, ... See full document
8
Semi Supervised Learning for Relation Extraction
... This paper proposes a semi-supervised learn- ing method for relation extraction. Given a small amount of labeled data and a large amount of unlabeled data, it first bootstraps a moderate number of weighted ... See full document
8
Distributed Semi-supervised Learning with Kernel Ridge Regression
... This paper provides error analysis for distributed semi-supervised learning with kernel ridge regression (DSKRR) based on a divide-and-conquer strategy. DSKRR applies kernel ridge regression (KRR) to ... See full document
22
Semi Supervised Learning of Concatenative Morphology
... In consequence, there has been a need for ap- proaches for morphological processing that would require little language-dependent resources. Due to this need, as well as the general interest in language acquisition and ... See full document
9
Deep Keyphrase Generation
... text, keyphrase i pairs for training, in which text refers to the concate- nation of the title and abstract of a publication, and keyphrase indicates an author-assigned key- ...initial learning rate ... See full document
11
DETECTION AND CLASSIFICATION OF DIABETIC RETINOPATHY USING ADAPTIVE BOOSTING AND ARTIFICIAL NEURAL NETWORK
... convolutional neural networks are designed and trained with different hyper- parameter values, changing behavior of the training curves are analyzed and the one with best evaluation metrics is ... See full document
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