Publications

Found 183 results
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Lowe, J.. B., Baker C. F., & Fillmore C. J. (1997).  A frame-semantic approach to semantic annotation. Proceedings of the SIGLEX Workshop on Tagging Text with Lexical Semantics: Why, What, and How?.
Lorenzo, A., Metere A., & Dzugutov M. (2018).  Hexatic smectic phase with algebraically decaying bond-orientational order.
López, J. Ferreiros, & Ellis D. P. W. (2000).  Using Acoustic Condition Clustering to Improve Acoustic Change Detection on Broadcast News. Proceedings of the 6th International Conference on Spoken Language Processing (ICSLP 2000). 4, 568-571.
Lopes, M.. E., Wang S.., & Mahoney M.. W. (2018).  Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap. Proceedings of the 35th ICML Conference. 3223-3232.
B. Loo, T., Hellerstein J. M., Huebsch R., Shenker S., & Stoica I. (2004).  Enhancing P2P File-Sharing with an Internet-Scale Query Processor. Proceedings of the 30th International Conference on Very Large Data Bases (VLDB 2004). 432-443.
Lönneker-Rodman, B., Baker C. F., & Hong J. (2008).  The New FrameNet Desktop: A Usage Scenario for Slovenian. 147-154.
Lönneker-Rodman, B., & Narayanan S. (2012).  Computational Models of Figurative Language.
Lönneker-Rodman, B. (2007).  Beyond Syntactic Valence: FrameNet Markup of Example Sentences in a Slovenian-German Online Dictionary. 152-164.
Lönneker-Rodman, B. (2008).  The Hamburg Metaphor Database Project: Issues in Resource Creation. Language Resources and Evaluation. 42(3), 293-318.
Lönneker-Rodman, B. (2007).  Multilinguality and FrameNet.
Lönneker-Rodman, B., & Baker C. F. (2009).  The FrameNet Model and Its Applications. Natural Language Engineering. 15(3), 415-453.
Lönneker-Rodman, B., & Narayanan S. (2010).  Computational Models of Figurative Language.
Long, J., Shelhamer E., & Darrell T. (2015).  Fully Convolutional Networks for Semantic Segmentation. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 3431-3440.
Lokshtanov, D., Mnich M., & Saurabh S. (2011).  Planar k-Path in Subexponential Time and Polynomial Space.
Livescu, K., Bezman A., Borges N., Yung L., etin Ö. Ç., Frankel J., et al. (2007).  Manual Transcription of Conversational Speech at the Articulatory Feature Level. 4, 953-956.
Livescu, K., etin Ö. Ç., Hasegawa-Johnson M., King S., Bartels C., Borges N., et al. (2007).  Articulatory Feature-Based Methods for Acoustic and Audio-Visual Speech Recognition: Summary from the 2006 Jhu Summer Workshop.
Liver, B., & Altmann J. (1997).  Social Carrier Recommendation for Selecting Services in Electronic Telecommunication Markets: A Preliminary Report.
Liu, Y., Chawla N.. V., Harper M. P., Shriberg E., & Stolcke A. (2006).  A Study in Machine Learning from Imbalanced Data for Sentence Boundary Detection in Speech. Computer Speech and Language. 20(4), 468-494.
Liu, J., Panda A., Singla A., P. Godfrey B., Schapira M., & Shenker S. (2013).  Ensuring Connectivity via Data Plane Mechanisms. 113-126.
Liu, Y., Shriberg E., Stolcke A., & Harper M. P. (2004).  Using Machine Learning to Cope with Imbalanced Classes in Natural Speech: Evidence from Sentence Boundary and Disfluency Detection. Proceedings of International Conference on Spoken Language Processing.
Liu, X., & Shapiro V. (2016).  Sample-Based Design of Functionally Graded Material Structures. Proceedings of the ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference.
Liu, C-G., Estrin D., Shenker S., & Zhang L. (1998).  Local error recovery in SRM: comparison of two approaches. Proceedings of IEEE/ACM Transactions on Networking. 6, 686-699.
Liu, J., Shenker S., Schapira M., & Yang B. (2011).  Data-Driven Network Connectivity. 1-6.
Liu, Y., Shriberg E., Stolcke A., Hillard D., Ostendorf M., & Harper M. P. (2006).  Enriching Speech Recognition with Automatic Detection of Sentence Boundaries and Disfluencies. IEEE Transactions on Audio. 14(5), 1526-1540.
Liu, B.., Jing L.., Li J.., Yu J.., Gittens A.., & Mahoney M.. W. (2018).  Group Collaborative Representation for Image Set Classification. International Journal of Computer Vision. 1-26.

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