frustratingly easy semi supervised domain adaptation

Ngày tải lên: 31/03/2014, 01:20

Ngày tải lên: 30/03/2014, 23:20

... nêu 26 Semi – Superviesd learning Chương II: HỌC NỬA GIÁM SÁT (Semi- supervised learning ) I. TỔNG QUAN 1.1 Giới thiệu về học có giám sát (supervised learning) và không có giám sát (unsupervised ... giải quyết bài toán. I. KẾT QUẢ BAN ĐẦU ĐÃ ĐẠT ĐƯỢC II. HƯỚNG PHÁT TRIỂN SEMI – SUPERVISED LEARNING MỤC LỤC Semi – supervised learning 1 Chương I: GIỚI THIỆU VỀ MÁY HỌC 4 ( Machine learning ... học máy Chương II: HỌC NỬA GIÁM SÁT (Semi- supervised learning ) I. TỔNG QUAN 1.1 Giới thiệu về học có giám sát (supervised learning) và không có giám sát (unsupervised learning) a. Học có giám...

Ngày tải lên: 25/04/2013, 19:30

... mỏy 12 Chng II: HC NA GIM ST 14 (Semi- supervised learning ) 14 I. TNG QUAN 14 1.1 Gii thiu v hc cú giỏm sỏt (supervised learning) v khụng cú giỏm sỏt (unsupervised learning) 14 a. Hc cú ... TRệẽC TUYEN Semi – Superviesd learning Nguyễn Ngọc Tùng – K54B - CNTT 14 Chương II: HỌC NỬA GIÁM SÁT (Semi- supervised learning ) I. TỔNG QUAN 1.1 Giới thiệu về học có giám sát (supervised ... Models trong Semi - supervised learning Generative Models thng c bit n vi vic gii quyt cỏc bi toỏn nhn dng nh, nhn dng vn bn, nhn dng ting núi THệ VIEN ẹIEN Tệ TRệẽC TUYEN Semi Superviesd...

Ngày tải lên: 27/04/2013, 21:02

... of Bayesian adaptation techniques [14], which adapt a usual event model to produce a number of unusual event models in an unsupervised manner. The proposed framework can thus be considered as a semi- supervised ... within each class. In the next subsection, we give more details on the used adaptation techniques. 3.2 MAP Adaptation Several adaptation techniques have been proposed for GMM-based HMMs, such as Gaussian ... Baseline Systems To evaluate the results, we compare the proposed semi- supervised framework with the following baseline systems. Supervised HMM: Two standard HMM models, one for usual events and...

Ngày tải lên: 19/02/2014, 18:20

... pre- vious unsupervised system, and unlike the super- vised and semi- supervised systems we mentioned, our model can be used for both unsupervised and semi- supervised mining in a consistent way. 3 Unsupervised ... with the unsupervised mining sys- tem of Sajjad et al. (2011), the best supervised and semi- supervised systems presented at NEWS10 (Kumaran et al., 2010b) and the best supervised and semi- supervised ... distribu- tion and require supervised /semi- supervised infor- mation for learning. We propose a flexible genera- tive model for transliteration mining usable for both unsupervised and semi- supervised learning. Previous...

Ngày tải lên: 19/02/2014, 19:20

... automatically. Fur- thermore, we apply domain adaptation, the pseudo-error sentences are from the source domain, and the real-error sentences are from the target domain. Experiments show that sta- ble ... in semi- supervised CRFs (Suzuki and Isozaki, 2008). It can appropriately correct new sentences while maintain- ing high accuracy on the training corpus. 3 Pseudo-error Sentences and Domain Adaptation The ... do- main adaptation technique. Namely, we regard the pseudo-error corpus as the source domain and the real-error corpus as the target domain, and models are learnt that fit the target domain. In...

Ngày tải lên: 19/02/2014, 19:20

... su- pervised NLP system to use these semi- supervised techniques. It is preferable to use a simple and general method to adapt existing supervised NLP systems to be semi- supervised. One approach that ... out-of -domain data than on the in -domain data. We were surprised by this result, because the OOD data was not even used during the unsupervised word representation induction, as was the in -domain ... CRFs. (In Suzuki et al. (2009), they extend their semi- supervised ap- proach to more general conditional models.) One of the advantages of the semi- supervised learning approach that we use is that...

Ngày tải lên: 20/02/2014, 04:20

... aspects with latent vari- ables. Note also that the proposed approach is orthogonal to semi- supervised and unsupervised induction of context independent (prior polarity) lexicons (Turney, 2002; ... advantage of both types of data on its own and jointly. Still, by comparing the fully supervised and the coarsely supervised models, the superior impact of fully labeled over coarsely labeled data ... y d with each input s i as well. 2 Combining coarse and full supervision The fully supervised and the partially supervised models both have their merits. The former requires an expensive and laborious...

Ngày tải lên: 20/02/2014, 05:20

... Simple, robust, scal- able semi- supervised learning via expectation regulariza- tion. In ICML. G. Mann and A. McCallum. 2008. Generalized expectation criteria for semi- supervised learning of conditional ... supervised CRF supervised CRF restricted GE CRF GE CRF GE human Figure 1: Comparison of the constraint baseline and both GE and supervised training of the restricted and full CRF. Note that supervised ... Methods for Un- supervised Discovery of Latent Structure in Natural Lan- guage Text. Ph.D. thesis, Johns Hopkins University. Qin Iris Wang, Dale Schuurmans, and Dekang Lin. 2008. Semi- supervised convex...

Ngày tải lên: 20/02/2014, 07:20

...  d characterizing the entailment information between them. 3 Graph Based Semi- Supervised Learning for Entailment Ranking We formulate semi- supervised entailment rank scores as follows. Let each data point ... California at Berkeley Berkeley, CA, 94720 zhiheng@eecs.berkeley.edu Abstract We present a graph-based semi- supervised learning for the question-answering (QA) task for ranking candidate sentences. Us- ing ... matching, question-type named-entity matching based on a question-classifier, etc. We implement a semi- supervised learning (SSL) approach to demonstrate that utilization of more unlabeled data points...

Ngày tải lên: 20/02/2014, 07:20

... explored semi- supervised or unsupervised approaches to the same problems, seeking to improve accuracy with the addition of lower cost unlabeled data. Tradi- tional approaches to semi- supervised ... linear-chain conditional random fields, a new semi- supervised training method that makes use of labeled features rather than labeled instances. Pre- vious semi- supervised methods have typically used ad-hoc ... CRF training and other semi- supervised methods when limited human effort is available. 1 Introduction A significant barrier to applying machine learning to new real world domains is the cost of...

Ngày tải lên: 20/02/2014, 09:20

... the testing set. Results for this method are presented later, in Table 5. 5.2 Semi- Supervised Method For the semi- supervised method we add unla- belled examples from monolingual corpora: the ... contains a par- tial cognate are: COG (cognate) and FF (false- friend). 5.1 Supervised Method For both the supervised and semi- supervised method we used the bag-of-words (BOW) ap- proach of modeling ... particular domain of Hansard and EuroParl. For this reason we used another set of automatically determined sen- tences from a multi -domain parallel corpus. The set of new sentences (multi -domain) ...

Ngày tải lên: 20/02/2014, 12:20

... semi- supervised named entity (NE) tagger. Our study addresses two questions: What types of syntactic features are suitable for extracting potential NEs to train a classi- fier in a semi- supervised ... experimental results suggest that a semi- supervised NE tagger can be success- fully developed using syntax-rich features. 2 Previous Works and Our Approach Supervised NE Tagging has been studied ... rely on a supervised learning framework where systems use large annotated training resources (Bikel et. al. 1999). These resources may not al- ways be available for non-English domains. This...

Ngày tải lên: 20/02/2014, 15:20

... learning fails on the DVD domain while on the three domains of book, electronic, and software, semi- supervised learning benefits slightly (p-value>0.05). In contrast, semi- supervised learning ... effectiveness of semi- supervised learning by comparing the baseline and co-training and single classifier . Figure 4 shows different results on different domains. Semi- supervised learning ... sentiment classification methods can be categorized into three types: unsupervised, supervised, and semi- supervised. Unsupervised methods involve deriving a sentiment classifier without any...

Ngày tải lên: 07/03/2014, 22:20

... class. This line of work has evolved to incorporate ideas from graph-based semi- supervised learning in extrac- tion from semi- structured text (Wang and Cohen, 2007), and in combining extractions ... 2007. Lightly -Supervised Attribute Extraction. NIPS 2007 Workshop on Machine Learning for Web Search. A. Carlson, J. Betteridge, R.C. Wang, E.R. Hruschka Jr, and T.M. Mitchell. 2010. Coupled Semi- Supervised Learning ... 11-16 July 2010. c 2010 Association for Computational Linguistics Experiments in Graph-based Semi- Supervised Learning Methods for Class-Instance Acquisition Partha Pratim Talukdar ∗ Search Labs,...

Ngày tải lên: 07/03/2014, 22:20

... is used to reduce tagging to a classification task. This simplifies semi- supervised training considerably. Our prefered semi- supervised method com- bines tri-training (Li and Zhou, 2005) and disagreement-based ... different semi- supervised methods. 5 Conclusion This paper first shows how stacking can be used to reduce POS tagging to a classification task. This reduction seems to enable robust semi- supervised learning. ... Raab, and Miroslav Spousta. 2009. Semi- supervised training for the averaged perceptron POS tagger. In EACL, Athens, Greece. Jun Suzuki and Hideki Isozaki. 2008. Semi- supervised sequential labeling...

Ngày tải lên: 07/03/2014, 22:20

Ngày tải lên: 08/03/2014, 00:20

Ngày tải lên: 08/03/2014, 01:20

Ngày tải lên: 08/03/2014, 01:20