[PDF] Top 20 Weakly supervised learning of allomorphy
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Weakly supervised learning of allomorphy
... In the realm of natural language processing, mor- phological segmentation is a well-researched and established problem (Goldsmith (2001), Creutz and Lagus (2005), Poon et al. (2009), Dreyer and Eisner (2011), Ruokolainen ... See full document
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Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions
... the learning and interpretation tasks, we also created a new dataset that includes only accurate in- structions labeled with a single, correct execution ...the learning approach and pro- vides a resource ... See full document
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Weakly Supervised Scene Parsing with Point-Based Distance Metric Learning
... We evaluate different methods quantitatively by using pixel accuracy and mIoU which describes the the precision of pre- diction and the average performance among all classes, re- spectively. We run multiple experiments ... See full document
8
Convex and Scalable Weakly Labeled SVMs
... Multi-instance learning (MIL) (Dietterich et ...multi-instance learning and semi-supervised learning has also been discussed in Zhou and Xu ... See full document
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Cross lingual Projected Expectation Regularization for Weakly Supervised Learning
... Projection-based methods can be very effective in weakly-supervised scenarios, as demonstrated by Yarowsky and Ngai (2001), and Xi and Hwa (2005). One problem with projected labels is that they are often ... See full document
12
Weakly Supervised Natural Language Learning Without Redundant Views
... Although co-training produces substantial improve- ments over the baseline at its best parameter settings, a closer examination of our results reveals that they cor- roborate previous findings: the algorithm is sensitive ... See full document
8
A Supertag Context Model for Weakly Supervised CCG Parser Learning
... real-world learning scenarios will always lack complete knowledge of the lexicon, we, too, want to allow for unknown words; for these, we assume the word may take any known ... See full document
10
Learning Representations for Weakly Supervised Natural Language Processing Tasks
... A growing body of theoretical and empirical evidence suggests that traditional, manually crafted features for a variety of NLP tasks limit systems’ performance in this weakly supervised learning for ... See full document
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Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data
... semi-supervised learning techniques that make it suitable for use in ...the learning process, in contrast to other methods which can require opaque supervision, such as carefully tuned ... See full document
30
Weakly Supervised Morphology Learning for Agglutinating Languages Using Small Training Sets
... of supervised and unsuper- vised induction techniques by achieving high per- formance on small amount of training ...Our weakly supervised approach is comparable with the supervised morphology ... See full document
8
Weakly-Supervised Hierarchical Text Classification
... train a set of local classifiers and make predictions in a top- down manner, or design global hierarchical loss functions that regularize with the hierarchy. Most existing efforts for hierarchical text classification ... See full document
8
Weakly Supervised Approaches for Ontology Population
... a weakly supervised approach to automatic Ontology Population from text and compare it with other two unsu- pervised ...is weakly supervised, since no annotated corpus is used in the ... See full document
8
Weakly supervised evidence pinpointing and description
... a weakly- supervised manner, ...descriptor learning problem [1, 2] in which the optimal feature descriptors are selected from a large candidate pool with various locations and ...stochastic ... See full document
13
Deep learning for whole slide image analysis : an overview
... Deep learning is already demonstrating its potential across a wide range of medical problems associated with digital ...strongly supervised techniques. Other techniques from weakly supervised, ... See full document
7
Weakly Supervised Concept based Adversarial Learning for Cross lingual Word Embeddings
... Comparison with unsupervised GANs As we have mentioned before, the preliminary mappings trained by the method of Lample et al. (2018) per- form well for some similar language pairs, such as Spanish to English and French ... See full document
12
Weakly Supervised Definition Extraction
... We refer now to unsupervised approaches to DE. (Reiplinger et al., 2012) benefit from hand crafted definitional patterns. Starting from a set of seed terms and patterns, term/definition pairs are itera- tively acquired, ... See full document
10
Transferable Curriculum for Weakly-Supervised Domain Adaptation
... Curriculum Learning (TCL) approach to weakly-supervised domain adaptation, extending from curriculum learning (Bengio et ...adversarial learning (Goodfellow et al. 2014). There are two ... See full document
8
Three phase training to address data sparsity in Neural Machine Translation
... combines weakly supervised and semi- supervised learning with NMT tech- niques to build a robust model using a limited amount of parallel ... See full document
10
Weakly Supervised Learning for Hedge Classification in Scientific Literature
... Recent years have witnessed a significant growth of research into weakly supervised ML techniques for NLP applications. Different approaches are of- ten characterised as either multi- or single-view, where ... See full document
8
Weakly supervised learning via statistical sufficiency
... this learning problem push for a different workaround manipulating loss ...out supervised learning almost as accurate as if its solution were ... See full document
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