Publications

Found 265 results
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D
Zaharia, M., Borthakur D., Sarma J. Sen, Elmeleegy K., Shenker S. J., & Stoica I. (2010).  Delay Scheduling: A Simple Technique for Achieving Locality and Fairness in Cluster Scheduling. 265-278.
Verma, D. C., Zhang H., & Ferrari D. (1991).  Delay Jitter Control for Real-Time Communication in a Packet Switching Network.
Omohundro, S. (1990).  The Delaunay Triangulation and Function Learning.
Fillmore, C. J. (1971).  Deixis 2. 70-90.
Fillmore, C. J. (1971).  Deixis 1. 38-49.
Weihrauch, K. (1992).  The Degrees of Discontinuity of Some Translators Between Representations ofthe Real Numbers.
Girshick, R., Iandola F., Darrell T., & Malik J. (2015).  Deformable Part Models are Convolutional Neural Networks. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 437-446.
Zhang, N., Farrell R., Iandola F., & Darrell T. (2013).  Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction.
McCauley, M., Zhao M., Jackson E. J., Raghavan B., Ratnasamy S., & Shenker S. J. (2016).  The Deforestation of L2.
Ertel, W. (1993).  On the Definition of Speedup.
Karp, R. M., Motwani R., & Raghaven P.. (1988).  Deferred Data Structuring. SIAM Journal on Computing. 17(5), 883-902.
Marczak, B. (2016).  Defending Dissidents from Targeted Digital Surveillance.
Vinyals, O., & Morgan N. (2013).  Deep vs. Wide: Depth on a Budget for Robust Speech Recognition.
Finn, C., Tan X. Yu, Duan Y., Darrell T., Levine S., & Abbeel P. (2016).  Deep spatial autoencoders for visuomotor learning. IEEE International Conference on Robotics and Automation (ICRA). 512-519.
Dodge, E. (2016).  A deep semantic corpus-based approach to metaphor analysis: A case study of metaphoric conceptualizations of poverty. MetaNet, Special Issue of Constructions and Frames. 8(2), 
Yu, S. X., & Zipser K. (2016).  A Deep Neural Net Trained for Person Categorization Develops Both Detailed Local Features and Broad Contexual Specificities. Poster at Vision Sciences Society Annual Meeting.
Gao, Y., Hendricks L. Anne, Kuchenbecker K. J., & Darrell T. (2016).  Deep learning for tactile understanding from visual and haptic data. IEEE International Conference on Robotics and Automation (ICRA). 536-543.
Andreas, J., Rohrbach M., Darrell T., & Klein D. (2016).  Deep compositional question answering with neural module networks. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
Hendricks, L. Anne, Venugopalan S., Rohrbach M., Mooney R., Saenko K., & Darrell T. (2016).  Deep Compositional Captioning: Describing Novel Object Categories Without Paired Training Data. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 1-10.
Morgan, N. (2012).  Deep and Wide: Multiple Layers in Automatic Speech Recognition. IEEE Transactions on Audio. 20(1), 7-13.
Morgan, N. (2011).  Deep and Wide: Multiple Layers in Automatic Speech Recognition.
Alizadeh, M., Yang S., Katti S., McKeown N., Prabhakar B., & Shenker S. J. (2012).  Deconstructing Datacenter Packet Transport. 133-138.
Fritz, M., & Schiele B. (2008).  Decomposition, Discovery, and Detection of Visual Categories Using Topic Models.
Barker, J., Cooke M. P., & Ellis D. P. W. (2000).  Decoding Speech in the Presence of Other Sound Sources. Proceedings of the 6th International Conference on Spoken Language Processing (ICSLP 2000).
M. Shokrollahi, A., & Wasserman H. (1998).  Decoding Algebraic-Geometric Codes Beyond the Error-Correction Bound.

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