... Japankuro@i.kyoto-u.ac.jpAbstractWe investigate activelearningmethods for Japanese dependency parsing. We propose active learningmethods of using partialdependency relations in a given sentence for parsing and evaluate ... algorithm.Machine Learning, 37(3):277–296.Robbie Haertel, Eric Ringger, Kevin Seppi, James Car-roll, and Peter McClanahan. 2008. Assessing thecosts of sampling methodsinactivelearningfor an-notation. ... that linguistic constraints have been shownuseful for reducing annotations inactive learning for NLP.Experimental results show that our proposed methods have improved considerably the learning curve...
... of CoNLL’03, pages 142–147.Katrin Tomanek and Udo Hahn. 2008. Approximating learning curves for active- learning- driven annotation. In Proceedings of LREC’08.Katrin Tomanek, Joachim Wermter, and ... active learningfor named entity recognition. In Proceedingsof ACL’04, pages 589–596.Min Tang, Xiaoqiang Luo, and Salim Roukos. 2001. Ac-tive learningfor statistical natural language parsing. In Proceedings ... selection for the NE task,while for the parsing task extrinsic selection per-formed markedly worse. This shows that examplesthat were very informative for the NE learner werenot that informative for...
... Sarkar. 2009. Active learningfor multilingual statistical machine trans-lation. In Proceedings of the Joint Conference ofthe 47th Annual Meeting of the ACL and the 4th In- ternational Joint Conference ... Association for Computational Linguistics.Katrin Tomanek and Udo Hahn. 2009. Semi-supervised activelearningfor sequence labeling. In Proceedings of the Joint Conference of the 47th An-nual Meeting ... costs of sampling methodsinactivelearningfor an-notation. In Proceedings of ACL-08: HLT, Short Pa-pers, pages 65–68, Columbus, Ohio, June. Associa-tion for Computational Linguistics.Gholamreza...
... (%)a-truePriora-truePredaFigure 3: Using true predominant sense for the 9nouns.the sense priors in WSJ. Using this new set of train-ing examples, we perform domain adaptation using active learning to obtain the curve ... training examples, we perform adaptation using active learning and obtain the a-truePrior curve in Figure 2. The a-truePrior curve shows that by en-suring that the sense priors in the BC training ... correct sense s for dminand add dminto DTΓ ← WSD system trained on new DTendFigure 1: Activelearning in Figure 1. In each iteration, we train a WSD sys-tem on the available training data...
... chemical industries in India is in leaps and bounds. Some of the major polluting chemical industries are fertilizer plants, tanneries, oil refineries, cement industries and dying industries. ... views of the labourers working in the dyeing and bleaching industries with the views of the locals of Tirupur who are not employed in these industries we find that the former have given many zeros ... scarcity of drinking water is due to pollution by these dyeing and bleaching industries of Tirupur, over population in slums due to the concentration of migrant labourers working in these industries....
... trans-form. In Proc. ICASSP.Andrew McCallum and Kamal Nigam. 1998. Employ-ing EM and pool-based activelearningfor text clas-sification. In Machine Learning: Proceedings of theFifteenth International ... toachieve a satisfactory performance using active learning. Active learning has been studied in the context of manynatural language processing (NLP) applications such asinformation extraction(Thompson ... clusteringresults in a better learning curve.4.4 Summary ResultFigure 8 shows the best activelearning result comparedwith that of random selection. The learning curve for ac-tive learning...
... burning zone and combustion 16 2.3 Determination of gas volume setpoint and temperature set point for CKD processing 26 2.4 Finding the MIX of raw materials in proper proportion and minimize ... μL(400) =0 min{[1,μVL(Z)]} min{[0,μM(Z)]} min{[0,μH(Z)]} μM(400)=1 min{[0, μL(Z)]} min{[1,μM(Z)]} min{[0,μH(Z)]} μH(400)=0 min{[0, μM(Z)]} min{[0,μH(Z)]} min{[0,μvH(Z)]} ... μVL(Z)]}, min {[1, μM(Z)],)], min {[0, μL(Z)]}, min {[0, μH(Z)]}, min {[0, μVH(Z)]}. We apply the mean of maximum method for defuzzification that is the intersection points of the line μ...
... multilingual sentence selection pro-tocols. In the multilingual setting, a novel co-training method foractivelearningin SMT is pro-posed using consensus translations which outper-forms ... strate-gies in the multilingual case. The ‘CombinedRank’ method outperforms all the other methods including the strong random selection baseline in both self-training and co-training modes. Thedisagreement-based ... AlternateCombineRankRandomFigure 4: The left/right plot show the performance of our AL methodsfor multilingual setting combined with self-training/co-training. The sentence selection methods from...
... confidenceestimators.3 ActiveLearningfor Sequence LabelingAL is a selective sampling technique where the learning protocol is in control of the data to beused for training. The intention with AL ... of the automatically labeled train-ing data is crucial for co-training to perform wellbecause too many tagging errors prevent a high-performing model from being learned. Also, thesize of the ... con-fidence in the predicted labels. Accordingly, ourapproach is a combination of AL and self-trainingto which we will refer as semi-supervised Active Learning (SeSAL) for sequence labeling.While...
... traditional learningmethodsin classrooms while delivering content mainly by using interactive multimedia CDs was termed hybrid e -learning. Using the same argument, the term hybrid digital library in ... A-level) examinations. Physics and Mathematics are the essential subjects required for admission for engineering training.1.1.5. Enrollment by Gender for Science and Engineering training in other ... E -learning e type of e -learning in the preceding section is termed as blended e -learning. Blending occurs when the traditional face-to-face meeting in classrooms is combined with training materials...
... CA.Kevin Duh and Katrin Kirchhoff. 2008. Beyond log-linear models: Boosted minimum error rate training for n-best ranking. In Proceedings of the 46th AnnualMeeting of the Association for Computational ... been content with tuning weights for largefeature sets on small development data. Ev-idence from machine learning indicates thatincreasing the training sample size results in better prediction. ... approach to scaling discrimina-tive learningfor SMT not only to large featuresets but also to large sets of parallel training data.Since inference for SMT (unlike many other learn-ing problems)...
... researchquestions or hypotheses;searching the literature;writing a proposal and applying for funding; anddealing with the organizational politics of research in clinical settings. In sharp contrast to the ... conducts clinical work as a form of appliedresearch.. The local clinical scientist, who applies a range of research methods andcritical thinking skills to solve local problems in clinical settings.. ... questions in advance ofdeveloping your procedures. Beginning researchers often rush into selecting themeasures that they will use before considering clearly what they really want tofind out. This inevitably...
... containing smiles and2,000 articles containing frowns were held-out asoptimising test data. We took increasing amountsof articles from the remaining dataset (from 2,000to 22,000 in increments ... numberbeing taken from the positive and negative sets) asoptimising training data. For each set of trainingdata we extracted a context of an increasing num-ber of tokens (from 10 to 1,000 in increments ... that more training data will im-prove the performance of the Emoticon-trained clas-sifiers by increasing the coverage. Potential sources for this include online bulletin boards, chat forums,and...
... and Kamal Nigam. 1998.Employing EM and pool-based activelearningfor textclassification. In Proceedings of the Fifteenth Interna-tional Conference on Machine Learning, pages 359–367.Grace ... Less is more: Ac-tive learning with support vector machines. In Pro-ceedings of the Seventeenth International Conferenceon Machine Learning. Hiroyuki Shinnou. 2000. Deterministic Japanese wordsegmentation ... parsing and information extraction. In Pro-ceedings of the Sixteenth International Conference onMachine Learning, pages 406–414.Simon Tong and Daphne Koller. 2000. Support vectormachine active...
... additional information on macroeconomic conditions – income growth and inflation; 6. Combination of econometric, smoothing and international average methods Data for total health spending in OECD ... importance of ageing in the increase in health expenditures per capita during the period from 1940 to 1990 in the United States. He found that that ageing, in the sense of an increasing proportion ... Moreover, with data on several of the intermediary inputs required for forecasting health spending even under the existing techniques missing in developing countries, it is easy to see that...