largescale costfocused active learning

... nhân người học, đảm bảo cho họ thích ứng với đời sống xà hội. TECHNIQUES THAT SUPPORT ACTIVE LEARNING  BRAINSTORMING  Free writing  Listing/bulleting  Clustering/mapping/webbing ... thiểu vai trò của người Khác Quá phục tùng Tự biến mình thành người vô hình Thờ ơ Active learning Một số biểu hiện cụ thể của người học theo hướng tích cực Người học biết làm chủ...

Ngày tải lên: 14/10/2013, 07:11

... directions. 2 Active Learning 2.1 Pool-based Active Learning Our base framework of active learning is based on the algorithm of (Lewis and Gale, 1994), which is called pool-based active learning. ... propose methods of improving active learning for parsing by using a smaller constituent than a sentence as a unit that is selected at each iteration of active learning. Typically in active learning for parsing ... important general framework of active learning, since the selection strategy with large mar- gin classifiers (Section 2.2) is much simpler and seems more practical for active learning in Japanese dependency...

Ngày tải lên: 20/02/2014, 04:20

... machine active learning with applications to text classification. Journal of Machine Learning Re- search (JMLR), 2:45–66. David Vickrey, Oscar Kipersztok, and Daphne Koller. 2010. An active learning ... stopping active learning based on stabi- lizing predictions and the need for user-adjustable stopping. In Proceedings of the Thirteenth Confer- ence on Computational Natural Language Learning (CoNLL-2009), ... Vijay-Shanker. 2009b. Tak- ing into account the differences between actively and passively acquired data: The case of active learning with support vector machines for imbal- anced datasets. In...

Ngày tải lên: 20/02/2014, 04:20

... tags, parse trees, and named entities. In this paper, we introduce multi-task active learning (MTAL), an active learning paradigm for multiple annotation tasks. We propose a new AL framework ... http://www.cis.upenn. edu/ ˜ dbikel/software.html. Leo Breiman. 1996. Bagging predictors. Machine Learning, 24(2):123–140. David A. Cohn, Zoubin Ghahramani, and Michael I. Jor- dan. 1996. Active learning with statistical models. Journal of Artificial ... 2004. Multi-criteria-based active learning for named entity recognition. In Proceedings of ACL’04, pages 589–596. Min Tang, Xiaoqiang Luo, and Salim Roukos. 2001. Ac- tive learning for statistical...

Ngày tải lên: 20/02/2014, 09:20

... each adaptation iteration. The adaptation process using active learning is represented by the curve a, while applying count-merging with active learning is rep- resented by the curve a-c. Note that ... al. (2006), where active learning was used successfully to reduce the annotation effort for WSD of 5 English verbs using coarse-grained evaluation. In that work, the authors only used active learning ... BC training examples and 406 WSJ adaptation examples per noun. 3 Active Learning For our experiments, we use naive Bayes as the learning algorithm. The knowledge sources we use include parts-of-speech,...

Ngày tải lên: 08/03/2014, 02:21

... through active learning, in which the next semantic input to annotate is de- termined by the current model. The probabilis- tic nature of BAGEL allows the use of certainty- based active learning ... certainty-based active learning, for different values of k. As our dataset only con- tains two paraphrases per dialogue act, the same dialogue act can only be queried twice during the active learning ... models trained on 40 utterances using active learning (p = .15 for naturalness and p = .41 for informativeness). These results sug- gest that certainty-based active learning is benefi- cial for training...

Ngày tải lên: 17/03/2014, 00:20

... slow and difficult. One popular solution is Active Learning, which maximizes learning accuracy while minimiz- ing labeling efforts. In active learning, the learning algorithm itself selects unlabeled ... selection criteria Active Confident Learning (ACL). 4 Evaluation To evaluate our active learning methods we used a similar experimental setup to Tong and Koller (2001). Each active learning algorithm ... and are fast to train — an important property for inter- active learning. Experimental validation on a num- ber of datasets shows that active learning with con- fidence can improve standard methods. 2...

Ngày tải lên: 17/03/2014, 02:20

... the test set. The ef- fectiveness of active learning is measured by comparing learning curves (i.e., test accuracy vs. number of training sentences ) of active learning and random selection. 4.1 ... clustering results in a better learning curve. 4.4 Summary Result Figure 8 shows the best active learning result compared with that of random selection. The learning curve for ac- tive learning is obtained ... time) required for a statistical parser to achieve a satisfactory performance using active learning. Active learning has been studied in the context of many natural language processing (NLP) applications...

Ngày tải lên: 17/03/2014, 08:20

... from passive learning, in which a classifier gets labeled examples randomly. Active learning is a general framework and does not depend on tasks or domains. It is expected that active learning will reduce ... 2001). Although there are many active learning methods with various classi- fiers such as a probabilistic classifier (McCallum and Nigam, 1998), we focus on active learning with Sup- port Vector ... that active learning works quite well and it significantly reduces labeled examples to be required. Let us see how many la- beled examples are required to achieve 96.0 % ac- curacy. In active learning...

Ngày tải lên: 17/03/2014, 08:20

... future work, we plan to incorporate trian- gulation into our active learning approach. 7 Conclusion This paper introduced the novel active learning task of adding a new language to an existing multi- lingual ... for active learning in the single language-pair setting which we then applied to the multilingual sentence selection pro- tocols. In the multilingual setting, a novel co- training method for active ... pair. In contrast, our co-training approach uses consensus translations and our setting for active learning is very differ- ent from their semi-supervised setting. A Ph.D. proposal by Chris Callison-Burch...

Ngày tải lên: 23/03/2014, 16:21

Ngày tải lên: 23/03/2014, 16:21

Ngày tải lên: 23/03/2014, 17:20

Ngày tải lên: 30/03/2014, 21:20

Ngày tải lên: 30/03/2014, 21:20

Ngày tải lên: 30/03/2014, 21:20

Ngày tải lên: 31/03/2014, 00:20

Ngày tải lên: 31/03/2014, 03:20

Ngày tải lên: 31/03/2014, 20:20

Ngày tải lên: 02/07/2014, 06:20

... sentences into active sentences. Our method separates training data for all input (source) particles and uses machine learning for each particle. We also used numerous rich features for learning. ... Passive/Causative Sentences into Active Sen- tences Using Machine Learning, pages 115–125. Springer Publisher. Masaki Murata, Qing Ma, and Hitoshi Isahara. 2002. Com- parison of three machine -learning methods ... passive sentences into active sentences. It separates training data into each input particle and uses machine learning for each particle. We also used numerous rich features for learning. Our method...

Ngày tải lên: 17/03/2014, 04:20