Publications

Found 4047 results
[ Author(Desc)] Title Type Year
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Y
Yegneswaran, V., Barford P., & Paxson V. (2005).  Using Honeynets for Internet Situational Awareness. Proceedings of the Fourth Workshop on Hot Topics in Networks (Hotnets-IV).
Yeh, T., Lee J. J., & Darrell T. (2009).  Fast Concurrent Object Localization and Recognition. 280-287.
Yeh, T., Lee J. J., & Darrell T. (2008).  Photo-Based Question Answering. 389-398.
Yeh, T., & Darrell T. (2008).  Dynamic Visual Category Learning.
Yeom, S., & Tschantz M. Carl (2018).  Discriminative but Not Discriminatory: A Comparison of Fairness Definitions under Different Worldviews. Proceedings of the 2018 Workshop on Privacy in the Electronic Society. 33-41.
Yiin-Chang, S., & Morgan N. (2016).  Robust CNN - based Speech Recognition With Gabor Filter Kernels. Proceedings of Interspeech 2016.
Yosef, N.., Gramm J., Wang Q.-F.., Noble W.. S., Karp R. M., & Sharan R. (2010).  Prediction of Phenotype Information from Genotype Data. Communications in Information and Systems. 10(2), 99-114.
Yoshida, M., Ikeda C., & Suzuki H. (1994).  An Evaluation of Burst-level Bandwidth Reservation Methods in WANEnvironments.
Yu, H., Breslau L., & Shenker S. (1999).  A Scalable Web Cache Consistency Architecture. Proceedings of the ACM Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication (SIGCOMM '99). 163-174.
Yu, S. X., & Lisin D. (2013).  Change Blindness Reveals Distinctive Featural Processing in Size, Color, and Orientation.
Yu, S. X. (2012).  Angular Embedding: A Robust Quadratic Criterion. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE. 34(1), 158-173.
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.
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.
Yu, D., Hinton G., Morgan N., Chien J-T., & Sagayama S. (2012).  Introduction to the Special Section on Deep Learning for Speech and Language Processing. IEEE Transactions on Audio. 20(1), 4-6.
Yuan, A., Luther K., Krause M., Vennix S. Isabel, Dow S. P., & Hartmann B. (2016).  Almost an expert: The effects of rubrics and expertise on perceived value of crowdsourced design critiques. Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. 1005-1017.
Z
Zagordi, O., Töpfer A., Prabhakaran S., Roth V., Halperin E., & Beerenwinkel N. (2012).  Probabilistic Inference of Viral Quasispecies Subject to Recombination. 342-354.
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.
Zaharia, M., Chowdhury M., Franklin M. J., Shenker S., & Stoica I. (2010).  Spark: Cluster Computing with Working Sets. 1-7.
Zaharia, M., Hindman B., Konwinski A., Ghodsi A., Joseph A. D., Katz R. H., et al. (2011).  The Datacenter Needs an Operating System. 1-5.
Zaharia, M., Katti S., Grier C., Paxson V., Shenker S., Stoica I., et al. (2012).  Hypervisors as a Foothold for Personal Computer Security: An Agenda for the Research Community.
Zaharia, M., Borthakur D., Sarma J. Sen, Elmeleegy K., Shenker S., & Stoica I. (2010).  Delay Scheduling: A Simple Technique for Achieving Locality and Fairness in Cluster Scheduling. 265-278.
Zaharia, M., Chowdhury M., Das T., Dave A., Ma J., McCauley M., et al. (2011).  Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing.
Zaharia, M., Chowdhury M., Das T., Dave A., Ma J., McCauley M., et al. (2012).  Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. 1-14.
Zaharia, M., Borthakur D., Sarma J. Sen, Elmeleegy K., Shenker S., & Stoica I. (2009).  Job Scheduling for Multi-User MapReduce Clusters.
Zaharia, M., Bolosky W. J., Curtis K., Fox A., Patterson D., Shenker S., et al. (2011).  Faster and More Accurate Sequence Alignment with SNAP.

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