Báo cáo khoa học: "Discriminative Learning for Joint Template Filling" pptx

... Association for Computational Linguistics, pages 845–853, Jeju, Republic of Korea, 8-14 July 2012. c 2012 Association for Computational Linguistics Discriminative Learning for Joint Template Filling Einat ... consis- tently strong performance on both mention de- tection and template filling tasks. 1 Introduction Information extraction (IE) systems recover struc- tured informatio...

Ngày tải lên: 30/03/2014, 17:20

... of the Association for Computational Linguistics, pages 316–324, Uppsala, Sweden, 11-16 July 2010. c 2010 Association for Computational Linguistics Discriminative Pruning for Discriminative ... ITG. For instance, there are two parses for three consecutive word pairs, viz. [/ [/ / ] ] and [[/ /] /] . The problem of re- dundancy is fixed by adopting ITG normal for...

Ngày tải lên: 20/02/2014, 04:20

... our learning algorithm is the strategy used to select samples for training. In general, this novel learning framework lies be- tween supervised learning and reinforcement learn- ing. Guided learning ... classification are dynamically incorporated in the learning phase. Guided learning is not as hard as reinforcement learning. At each local step in learning, we always know the u...

Ngày tải lên: 20/02/2014, 12:20

... systems adopting the standard machine learning approach, outperforming them by as much as 4–7% on the three data sets for one of the performance metrics. 2 Related Work As mentioned before, our approach differs ... and Cardie (2002b) for details. Learning algorithms. We consider three learning algorithms, namely, the C4.5 decision tree induction system (Quinlan, 1993), the RIPPER ru...

Ngày tải lên: 20/02/2014, 15:20

... applying it to our specific task. 3.1 Learning Model The framework from which HM-SVM are derived is a maximum margin formulation for joint fea- ture functions in kernel learning setting. Given n labeled ... satisfactory for practical use. The limitation is even more pertinent for the lan- guages that do not have sophisticated parsing re- sources, or languages that have inherent lin...

Ngày tải lên: 08/03/2014, 01:20

... Linguistics, pages 25–32, Prague, Czech Republic, June 2007. c 2007 Association for Computational Linguistics Transductive learning for statistical machine translation Nicola Ueffing National Research Council ... Algorithm 1 we run it for a fixed number of iterations and instead focus on finding useful def- initions for Estimate, Score and Select that can be experimentally shown to im...

Ngày tải lên: 08/03/2014, 02:21

... paper we study spectral learning methods for non-deterministic split head- automata grammars, a powerful hidden- state formalism for dependency parsing. We present a learning algorithm that, ... integer linear programming formulations for dependency parsing. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on...

Ngày tải lên: 08/03/2014, 21:20

... contrast, our emphasis is on learning language by proactively interacting with an external environment. Reinforcement Learning for Language Pro- cessing Reinforcement learning has been previ- ously ... divided into 70 for training, 18 for development, and 40 for test. In the puzzle game domain, we use 50 tutorials, divided into 40 for training and 10 for test. 9 Statistics...

Ngày tải lên: 17/03/2014, 01:20

... 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 ... avoid the unwanted bias toward small clusters. For cluster , the weight for sample is proportional to . Weight by Performance: The idea of weight by performance is to focu...

Ngày tải lên: 17/03/2014, 08:20

Ngày tải lên: 23/03/2014, 14:20