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 
E
Eddy, W. M., & Allman M. (2002).  A Comparison of RED's Byte and Packet Modes.
Eddy, W. M., & Allman M. (2000).  Advantages of Parallel Processing and the Effects of Communications Time.
D
Dutta, P., Culler D. E., & Shenker S. J. (2008).  Asynchronous Neighbor Discovery: Finding Needles of Connectivity in Haystacks of Time. 531-532.
Dutta, P., Culler D. E., & Shenker S. J. (2007).  Procrastination Might Lead to a Longer and More Useful Life. 1-7.
Durumeric, Z., Li F., Kasten J., Amann J., Beekman J., Payer M., et al. (2014).  The Matter of Heartbleed.
[Anonymous] (2001).  Developments in Forecast Combination and Portfolio Choice. (Dunis, C.., Timmermann A.., & Moody J., Ed.).
Dunietz, J., Levin L., & Petruck M. R. L. (2017).  Construction Detection in a Conventional NLP Pipeline. Proceedings of the AAAI 2017 Spring Symposium on Computational Construction Grammar and Natural Language Understanding. 178-184.
Duffield, N., Presti F. Lo, Paxson V., & Towsley D. (2006).  Network Loss Tomography Using Striped Unicast Probes. IEEE/ACM Transactions on Networking. 697-710.
Duffield, N., Presti F. Lo, Paxson V., & Towsley D. (2001).  Inferring Link Loss Using Striped Unicast Probes. Proceedings of IEEE INFOCOM.
Duan, H., Weaver N., Zhao Z., Hu M., Liang J., Jiang J., et al. (2012).  Hold-On: Protecting Against On-Path DNS Poisoning.
Drivonikou, V. G., Kay P., Regier T., Ivry R. B., Gilbert A. L., Franklin A., et al. (2007).  Further Evidence That Whorfian Effects Are Stronger in the Right Visual Field Than the Left. 104(3), 1097-1102.
Drineas, P., & Mahoney M. (2016).  RandNLA: Randomized Numerical Linear Algebra. Communications of the ACM. 59, 80-90.
Dries, A., & Rückert U. (2009).  Adaptive Concept Drift Detection. 235-246.
Dreger, H., Feldmann A., Paxson V., & Sommer R. (2008).  Predicting the Resource Consumption of Network Intrusion Detection Systems. 135-154.
Dreger, H., Feldmann A., Paxson V., & Sommer R. (2004).  Operational Experiences with High-Volume Network Intrusion Detection. Proceedings of the 11th ACM Conference on Computer Communications Security (CCS 2004). 11, 2.
Dreger, H., Feldmann A., Mai M.., Paxson V., & Sommer R. (2006).  Dynamic Application-Layer Protocol Analysis for Network Intrusion Detection. Proceedings of the 15th USENIX Security Symposium (Security '06).
Dreger, H., Kreibich C., Paxson V., & Sommer R. (2005).  Enhancing the Accuracy of Network-Based Intrusion Detection with Host-Based Context. Proceedings of Conference on Detection of Intrusions and Malware and Vulnerability Assessment (DIMVA 2005). 206-221.
Doubleday, S., Trott S., & Feldman J. (2017).  Processing Natural Language About Ongoing Actions in ECG. Proceedings of the AAAI 2017 Spring Symposium on Computational Construction Grammar and Natural Language Understanding.
Dorigo, M. (1992).  Genetic and Non Genetic Operators in Alecsys - Revised Version.
Donoho, D.., Flesia A.. G., Shankar U., Paxson V., Coit J.., & Staniford S. (2002).  Multiscale Stepping-Stone Detection: Detecting Pairs of Jittered Interactive Streams by Exploiting Maximum Tolerable Delay. Proceedings of RAID.
Dong, Z.., Yao Z.., Gholami A.., Mahoney M., & Keutzer K.. (2019).  HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision. Proceedings of ICCV 2019.
Donahue, J., Hendricks L. Anne, Guadarrama S., Rohrbach M., Venugopalan S., Saenko K., et al. (2015).  Long-Term Recurrent Convolutional Networks for Visual Recognition and Description.
Donahue, J., Hoffman J., Rodner E., Saenko K., & Darrell T. (2013).  Semi-Supervised Domain Adaptation with Instance Constraints.
Donahue, J., Jia Y., Vinyals O., Hoffman J., Zhang N., Tzeng E., et al. (2014).  DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition.
Donahue, J., Krahenbuhl P., & Darrell T. (2016).  Adversarial Feature Learning. CoRR. abs/1605.09782,

Pages