Index of papers in Proc. ACL 2009 that mention
• objective function
Lin, Dekang and Wu, Xiaoyun
 Discussion and Related Work Ando and Zhang (2005) defined an objective function that combines the original problem on the labeled data with a set of auxiliary problems on unlabeled data. Discussion and Related Work The combined objective function is then alternatingly optimized with the labeled and unlabeled data. Introduction The learning algorithm then optimizes a regularized, convex objective function that is expressed in terms of these features. Introduction distributed clustering algorithm with a similar objective function as the Brown algorithm. Query Classification We made a small modification to the objective function for logistic regression to take into account the prior distribution and to use 50% as a uniform decision boundary for all the classes. Query Classification When training the classifier for a class with [9 positive examples out of a total of n examples, we change the objective function to: Query Classification We suspect that such features make the optimization of the objective function much more difficult.
objective function is mentioned in 7 sentences in this paper.
Topics mentioned in this paper:
Tsuruoka, Yoshimasa and Tsujii, Jun'ichi and Ananiadou, Sophia
 Introduction Also, SGD is very easy to implement because it does not need to use the Hessian information on the objective function . Log-Linear Models SGD uses a small randomly-selected subset of the training samples to approximate the gradient of the objective function given by Equation 2. Log-Linear Models The learning rate parameters for SGD were then tuned in such a way that they maximized the value of the objective function in 30 passes. Log-Linear Models Figure 3 shows how the value of the objective function changed as the training proceeded.
objective function is mentioned in 6 sentences in this paper.
Topics mentioned in this paper:
Druck, Gregory and Mann, Gideon and McCallum, Andrew
 Abstract Model parameters are estimated using a generalized expectation (GE) objective function that penalizes the mismatch between model predictions and linguistic expectation constraints. Generalized Expectation Criteria Generalized expectation criteria (Mann and McCallum, 2008; Druck et al., 2008) are terms in a parameter estimation objective function that express a preference on the value of a model expectation. Generalized Expectation Criteria 2In general, the objective function could also include the likelihood of available labeled data, but throughout this paper we assume we have no parsed sentences. Introduction With GE we may add a term to the objective function that encourages a feature-rich CRF to match this expectation on unlabeled data, and in the process learn about related features.
objective function is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Jiang, Jing
 A multitask transfer learning solution We learn the optimal weight vectors {fikfifzv fiT and 3 by optimizing the following objective function: A multitask transfer learning solution The objective function follows standard empirical risk minimization with regularization. A multitask transfer learning solution Recall that we impose a constraint FV = 0 when optimizing the objective function .
objective function is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Ravi, Sujith and Knight, Kevin
 Discussion In MDL, there is a single objective function to (1) maximize the likelihood of observing the data, and at the same time (2) minimize the length of the model description (which depends on the model size). Discussion However, the search procedure for MDL is usually nontrivial, and for our task of unsupervised tagging, we have not found a direct objective function which we can optimize and produce good tagging results. Small Models Finally, we add an objective function that minimizes the number of grammar variables that are assigned a value of 1. Small Models objective function value of 459.3
objective function is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Haffari, Gholamreza and Sarkar, Anoop
 AL-SMT: Multilingual Setting This goal is formalized by the following objective function: AL-SMT: Multilingual Setting The nonnegative weights ad reflect the importance of the different translation tasks and 2d ad 2 l. AL-SMT formulation for single language pair is a special case of this formulation where only one of the ad’s in the objective function (1) is one and the rest are zero. Sentence Selection: Multiple Language Pairs The goal is to optimize the objective function (1) with minimum human effort in providing the translations.
objective function is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Yang, Qiang and Chen, Yuqiang and Xue, Gui-Rong and Dai, Wenyuan and Yu, Yong
 Image Clustering with Annotated Auxiliary Data Based on the graphical model representation in Figure 3, we derive the log-likelihood objective function , in a similar way as in (Cohn and Hofmann, 2000), as follows Image Clustering with Annotated Auxiliary Data objective function ignores all the biases from the Image Clustering with Annotated Auxiliary Data points based on the objective function £ in Equation (5).
objective function is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Zaslavskiy, Mikhail and Dymetman, Marc and Cancedda, Nicola
 Conclusion SMT comparably or better than the state-of-the-art beam-search strategy, converging on solutions with higher objective function in a shorter time. Experiments Both algorithms do not show any clear score improvement with increasing running time which suggests that the decoder’s objective function is not very well correlated with the BLEU score on this corpus. The Traveling Salesman Problem and its variants LK works by generating an initial random feasible solution for the TSP problem, and then repeatedly identifying an ordered subset of k edges in the current tour and an ordered subset of k edges not included in the tour such that when they are swapped the objective function is improved.
objective function is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Zhao, Shiqi and Lan, Xiang and Liu, Ting and Li, Sheng
 Statistical Paraphrase Generation In SMT, however, the optimization objective function in MERT is the MT evaluation criteria, such as BLEU. Statistical Paraphrase Generation We therefore introduce a new optimization objective function in this paper. Statistical Paraphrase Generation Replacement f-measure (rf): We use rf as the optimization objective function in MERT, which is similar to the conventional f-measure and lever-agesrp and rr: 7“f = (2 X 7”]?
objective function is mentioned in 3 sentences in this paper.
Topics mentioned in this paper: