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» Quality and perceived usefulness of process models
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ACL
2010
14 years 7 months ago
Hierarchical Joint Learning: Improving Joint Parsing and Named Entity Recognition with Non-Jointly Labeled Data
One of the main obstacles to producing high quality joint models is the lack of jointly annotated data. Joint modeling of multiple natural language processing tasks outperforms si...
Jenny Rose Finkel, Christopher D. Manning
KDD
2007
ACM
124views Data Mining» more  KDD 2007»
15 years 4 months ago
Hierarchical mixture models: a probabilistic analysis
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Mark Sandler
SIGIR
2008
ACM
14 years 9 months ago
A study of learning a merge model for multilingual information retrieval
This paper proposes a learning approach for the merging process in multilingual information retrieval (MLIR). To conduct the learning approach, we also present a large number of f...
Ming-Feng Tsai, Yu-Ting Wang, Hsin-Hsi Chen
ICML
2007
IEEE
15 years 10 months ago
Beamforming using the relevance vector machine
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...
David P. Wipf, Srikantan S. Nagarajan
ICPR
2010
IEEE
15 years 1 months ago
Improving Undersampled MRI Reconstruction Using Non-Local Means
Obtaining high quality images in MR is desirable not only for accurate visual assessment but also for automatic processing to extract clinically relevant parameters. Filtering-bas...
Ganesh Adluru, Tolga Tasdizen, Ross Whitaker, Edwa...