Publications

Found 4228 results
[ Author(Asc)] Title Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
Z
Zhang, N., Shelhamer E., Gao Y., & Darrell T. (2015).  Fine-grained pose prediction, normalization, and recognition. CoRR. abs/1511.07063,
Zhang, N., Farrell R., & Darrell T. (2012).  Pose Pooling Kernels for Sub-Category Recognition. 3665-3672.
Zhang, H., & Keshav S. (1991).  Large Comparison of Rate-Based Service Disciplines.
Zhang, J. (1991).  The Mean Field Theory in EM Procedures for Markov Random Fields.
Zhang, H., & Ferrari D. (1992).  Rate-Controlled Static Priority Queueing.
Zhang, Y., Paxson V., & Shenker S. J. (2000).  The Stationarity of Internet Path Properties: Routing, Loss, and Throughput.
Zhang, Y., Breslau L., Paxson V., & Shenker S. J. (2002).  On the Characteristics and Origins of Internet Flow Rates. ACM SIGCOMM Computer Communication Review. 32(4), 309-322.
Zhang, W., Fang V., Panda A., & Shenker S. J. (2020).  Kappa: a programming framework for serverless computing. SoCC '20: Proceedings of the 11th ACM Symposium on Cloud Computing. 328-343.
Zhang, H., & Knightly E. W. (1994).  Comparison of Rate-Controlled Static Priority and Stop-and-Go.
Zhang, N., Farrell R., Iandola F., & Darrell T. (2013).  Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction.
Zhang, M., Karp B., Floyd S., & Peterson L. (2002).  Improving TCP's Performance Under Reordering with DSACK.
Zhang, N., Donahue J., Girshick R., & Darrell T. (2014).  Part-Based R-CNNs for Fine-Grained Category Detection.
Zhang, T.., Yao Z.., Gholami A.., Keutzer K.., Gonzalez J.., Biros G.., et al. (2019).  ANODEV2: A Coupled Neural ODE Evolution Framework. Proceedings of the 2019 NeurIPS Conference.
Zhang, Y., & Paxson V. (2000).  Detecting Stepping Stones. Proceedings of the Ninth USENIX Security Symposium.
Zeiler, S., Meutzner H., Abdelaziz A. Hussen, & Kolossa D. (2016).  Introducing the Turbo-Twin-HMM for Audio-Visual Speech Enhancement. Proceedings of Interspeech 2016.
Zaslavsky, N., Garvin K., Kemp C., Tishby N., & Regier T. (2019).  Evolution and efficiency in color naming: The case of Nafaanra. Proceedings of the 41st Annual Meeting of the Cognitive Science Society.
Zaslavsky, N., Kemp C., Tishby N., & Regier T. (2019).  Communicative need in colour naming. Cognitive Neuropsychology.
Zaslavsky, N., Regier T., Tishby N., & Kemp C. (2019).  Semantic categories of artifacts and animals reflect efficient coding. Proceedings of the 41st Annual Meeting of the Cognitive Science Society.
Zarchy, D., Mittal R., Schapira M., & Shenker S. J. (2019).   Axiomatizing Congestion Control. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 3(2), 
Zamir, O.., Etzioni O., Madani O.., & Karp R. M. (1997).  Fast and Intuitive Clustering of Web Documents. Proceedings of the Third International Conference on Knowledge Discovery and Data Mining. 287-290.
Zaitlen, N., Kang H. Min, Feolo M. L., Sherry S. T., Halperin E., & Eskin E. (2005).  Inference and Analysis of Haplotypes from Combined Genotyping Studies Deposited in dbSNP. Genome Research. 15(11), 1594-1600.
Zaitlen, N., Pasaniuc B., Gur T., Ziv E., & Halperin E. (2010).  Leveraging Genetic Variability Across Populations for the Identification of Causal Variants. The American Journal of Human Genetics. 86(1), 23-33.
Zaitlen, N., Kang H. Min, Eskin E., & Halperin E. (2007).  Leveraging the HapMap Correlation Structure in Association Studies. American Journal of Human Genetics. 80, 683-691.
Zaharia, M., Xin R. S., Wendell P., Das T., Armbrust M., Dave A., et al. (2016).  Apache Spark: a unified engine for big data processing. Communications of the ACM. 59(11), 56-65.
Zaharia, M., Chowdhury M., Das T., Dave A., Ma J., McCauley M., et al. (2012).  Fast and Interactive Analytics Over Hadoop Data with Spark. USENIX ;login:. 34(4), 45-51.

Pages