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Multi-Step Regression Learning for Compositional Distributional Semantics.

, , , , and . IWCS, page 131-142. The Association for Computer Linguistics, (2013)

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A Simple Approach for HPSG Supertagging Using Dependency Information., , and . HLT-NAACL, page 645-648. The Association for Computational Linguistics, (2010)Multi-Step Regression Learning for Compositional Distributional Semantics., , , , and . IWCS, page 131-142. The Association for Computer Linguistics, (2013)Enhancing breakpoint resolution with deep segmentation model: A general refinement method for read-depth based structural variant callers., , , and . PLoS Comput. Biol., (2021)On the application of BERT models for nanopore methylation detection., , , , , , and . BIBM, page 320-327. IEEE, (2021)Probabilistic Chinese word segmentation with non-local information and stochastic training., , , , and . Inf. Process. Manage., 49 (3): 626-636 (2013)Cooperative reconnaissance mission planning for heterogeneous UAVs with DCSA., , , , and . ICCA, page 417-422. IEEE, (2019)Structure-guided supertagger learning., , and . Natural Language Engineering, 18 (2): 205-234 (2012)Reconstruction of high read-depth signals from low-depth whole genome sequencing data using deep learning., , , and . BIBM, page 1227-1232. IEEE Computer Society, (2017)A Discriminative Latent Variable Chinese Segmenter with Hybrid Word/Character Information., , , , and . HLT-NAACL, page 56-64. The Association for Computational Linguistics, (2009)Forest-guided Supertagger Training., , and . COLING, page 1281-1289. Tsinghua University Press, (2010)