Publications

Found 110 results
Author Title Type [ Year(Desc)]
Filters: First Letter Of Title is H  [Clear All Filters]
2015
Vallina-Rodriguez, N., Sundaresan S., Kreibich C., & Paxson V. (2015).  Header Enrichment or ISP Enrichment: Emerging Privacy Threats in Mobile Networks.
2016
Liu, X., & Shapiro V. (2016).  Homogenization of material properties in additively manufactured structures. Computer-Aided Design. 78, 71-82.
Chen, J., Weaver N., Jiang J., Wan T., Duan H., & Paxson V. (2016).   Host of Troubles: Multiple Host Ambiguities in HTTP Implementations. Proceedings of ACM CCS.
Ravuri, S., & Wegmann S. (2016).  How neural network depth compensates for HMM conditional independence assumptions in DNN-HMM acoustic models. Proceedings of Interspeech 2016.
2017
Qazi, Z. Ayyub, Walls M., Panda A., Sekar V., Ratnasamy S., & Shenker S. (2017).  A High Performance Packet Core for Next Generation Cellular Networks.. Proceedings of the Conference of the ACM Special Interest Group on Data Communication SIGNCOMM '17.
2018
Yao, Z.., Gholami A.., Lei Q.., Keutzer K.., & Mahoney M.. W. (2018).  Hessian-based Analysis of Large Batch Training and Robustness to Adversaries. Proceedings of the 2018 NeurIPS Conference. 4954-4964.
Lorenzo, A., Metere A., & Dzugutov M. (2018).  Hexatic smectic phase with algebraically decaying bond-orientational order.
2019
Dong, Z.., Yao Z.., Gholami A.., Mahoney M. W., & Keutzer K.. (2019).  HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision. Proceedings of ICCV 2019.
Shapiro, V., & Liu X. (2019).  Homogenization of material properties in additively manufactured structures. US Patent 10353378.
2020
Martin, C.. H., & Mahoney M. W. (2020).  Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks. Proceedings of 2020 SDM Conference.

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