[PDF] Top 20 Structured Prediction via Output Space Search
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Structured Prediction via Output Space Search
... our output space search framework, the role of the cost function C is to eval- uate the complete outputs that are uncovered by the search ...the search procedure as a type of heuristic ... See full document
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Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels
... to Output Kernel Regression that present two additional properties compared to OK3-based methods: namely, models are able to take into account structure in input data and can be learned within the framework of ... See full document
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Distilling Knowledge for Search based Structured Prediction
... Like in the parsing experiments, sharpen the distribution when exploring the search space is more helpful to the model’s performance but the differences when T ≤ 0.2 is not significant as shown in Figure 3. ... See full document
10
Search based Structured Prediction applied to Biomedical Event Extraction
... a structured prediction problem in which the output for a given instance is a (possibly disconnected) di- rected acyclic graph (not necessarily a tree) in which vertices correspond to triggers or ... See full document
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Biomedical event extraction from abstracts and full papers using search-based structured prediction
... a structured prediction problem in which the output for a given instance is a (possibly disconnected) directed acyclic graph (not necessarily a tree) in which vertices correspond to triggers or ... See full document
11
Joint Event Extraction via Structured Prediction with Global Features
... to search for the best configuration under the current ...exact search in our framework be- cause: (1) by jointly modeling the trigger labeling and argument labeling, the search space becomes ... See full document
10
Structured Sparsity in Structured Prediction
... employed structured sparsity in com- putational ...the output space, and structure in the feature ...ing structured predictors with high predictive power, while reducing manual feature ... See full document
12
Enabling More Accurate and Efficient Structured Prediction
... label space, such that at the leave nodes only comparison between a small number of classes is ...the output space, the tree maintains and repeatedly filters only a single ... See full document
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Biomedical Event Extraction from Abstracts and Full Papers using Search based Structured Prediction
... with prediction- based ...the output of the parser of Charniak and Johnson (2005) adapted to the biomedical domain by Mc- Closky (2010), as provided by the shared task orga- nizers in the Stanford collapsed ... See full document
5
Structured Perceptron with Inexact Search
... Discriminative structured prediction algorithms such as conditional random fields (Lafferty et ...2001), structured perceptron (Collins, 2002), max- margin markov networks (Taskar et ...many ... See full document
10
Magic Moments for Structured Output Prediction
... DLAs directly learn the model parameters such that the accuracy of the prediction is somehow optimized. All these algorithms are in some sense empirical risk minimizers, in that they optimize the prediction ... See full document
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Towards structured output prediction of enzyme function
... The marginal dual problem is solved by the conditional gradient algorithm (c.f. [22]) that iteratively the best fea- sible direction given the current gradient and uses line search to locate the optimal point in ... See full document
10
Structured Prediction with Output Embeddings for Semantic Image Annotation
... the output of several vision systems to produce input for a language gen- eration ...“meaning” space, represented by semantic tuples which are very similar to our ...representation space, in which ... See full document
6
Large Margin Methods for Structured and Interdependent Output Variables
... and output spaces is one of the key challenges in computational ...dependent output variables, structured output spaces, and classification problems with class ...of output spaces ... See full document
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SPARSE: Structured Prediction using Argument Relative Structured Encoding
... Word Representations To understand the effect of pretraining given its pervasive success through- out NLP as well as the extent to which domain- specific LSTM encoders are beneficial, we per- form experiments on the ... See full document
5
Stability and Generalization in Structured Prediction
... The remainder of this paper is organized as follows. Section 2 introduces the notation used throughout the paper and reviews some background in structured prediction, templated Markov random fields, ... See full document
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Object Search: Supporting Structured Queries in Web Search Engines
... of structured information is embedded in web pages in disparate ...General search engines (GSEs) do not support queries over these types of data because they ignore the web document ...through ... See full document
9
Learning Ensembles of Structured Prediction Rules
... local prediction (Cortes et al., 2014a). En- semble methods for structured prediction based on bagging, random forests and random subspaces have also been proposed in (Kocev et ...the ... See full document
12
A Study of Latent Structured Prediction Approaches to Passage Reranking
... could still find an exact solution to the hinge-loss relaxation of Average Precision (AP) for the struc- tural SVM approach. It is found for the partic- ular case of a combined feature mapping of in- puts and ... See full document
11
The use of the Kalman filter in the automated segmentation of EIT lung images
... Data were collected from a group of 10 male subjects with no known respiratory or cardiac abnormalities (age: mean 32; age range: 27-42). In each case, a 16 electrode adjacent protocol was chosen, and 16 electrodes were ... See full document
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