Publications

Found 4258 results
Author [ Title(Desc)] Type Year
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Alizadeh, M., Yang S., Katti S., McKeown N., Prabhakar B., & Shenker S. J. (2012).  Deconstructing Datacenter Packet Transport. 133-138.
Morgan, N. (2011).  Deep and Wide: Multiple Layers in Automatic Speech Recognition.
Morgan, N. (2012).  Deep and Wide: Multiple Layers in Automatic Speech Recognition. IEEE Transactions on Audio. 20(1), 7-13.
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.
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).
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.
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.
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), 
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.
Vinyals, O., & Morgan N. (2013).  Deep vs. Wide: Depth on a Budget for Robust Speech Recognition.
Marczak, B. (2016).  Defending Dissidents from Targeted Digital Surveillance.
Karp, R. M., Motwani R., & Raghaven P.. (1988).  Deferred Data Structuring. SIAM Journal on Computing. 17(5), 883-902.
Ertel, W. (1993).  On the Definition of Speedup.
McCauley, M., Zhao M., Jackson E. J., Raghavan B., Ratnasamy S., & Shenker S. J. (2016).  The Deforestation of L2.
Zhang, N., Farrell R., Iandola F., & Darrell T. (2013).  Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction.
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.
Weihrauch, K. (1992).  The Degrees of Discontinuity of Some Translators Between Representations ofthe Real Numbers.
Fillmore, C. J. (1971).  Deixis 1. 38-49.
Fillmore, C. J. (1971).  Deixis 2. 70-90.
Omohundro, S. (1990).  The Delaunay Triangulation and Function Learning.
Verma, D. C., Zhang H., & Ferrari D. (1991).  Delay Jitter Control for Real-Time Communication in a Packet Switching Network.
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.
Fernández-Iglesias, M. J., Pavón-Marino P., Rodríguez J.., Rifon L. Anido, & Llamas-Nistal M. (2000).  DelfosnetX: A Workbench for XML-Based Information Retrieval Systems. Proceedings of the 7th International Symposium on String Processing and Information Retrieval. 87-95.
Luo, Z., Fu S., Theis M., Hasan S., Ratnasamy S., & Shenker S. (2021).  Democratizing cellular access with CellBricks. SIGCOMM '21: Proceedings of the 2021 ACM SIGCOMM 2021 Conference.
Iandola, F., Moskewicz M., Karayev S., Girshick R., Darrell T., & Keutzer K. (2014).  DenseNet: Implementing Efficient ConvNet Descriptor Pyramids.

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