Publications

Found 4258 results
Author Title Type [ Year(Asc)]
2015
Marczak, B., Weaver N., Dalek J., Ensafi R., Fifield D., McKune S., et al. (2015).  An Analysis of China’s “Great Cannon”. Proceedings of the USENIX Workshop on Free and Open Communications on the Internet (FOCI).
Wijesekera, P., Baokar A., Hosseini A., Egelman S., Wagner D., & Beznosov K. (2015).  Android Permissions Remystified: A Field Study on Contextual Integrity. Proceedings of the 24th USENIX Security Symposium.
Tsai, T.. J. (2015).  Are You TED Talk Material? Comparing Prosody in Professors and TED Speakers.
Ashraf, K., Elizalde B. Martinez, Iandola F., Moskewicz M., Bernd J., Friedland G., et al. (2015).  Audio-Based Multimedia Event Detection with DNNs and Sparse Sampling. 611-614.
Datta, A., Tschantz M. Carl, & Datta A. (2015).  Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination. Proceedings on Privacy Enhancing Technologies. 2015(1), 92-112.
Azadi, S., Feng J., Jegelka S., & Darrell T. (2015).  Auxiliary Image Regularization for Deep CNNs with Noisy Labels. CoRR. abs/1511.07069,
Miller, B., Kantchelian A., Tschantz M. Carl, Afroz S., Bachwani R., Faizullabhoy R., et al. (2015).  Back to the Future: Malware Detection with Temporally Consistent Labels. CoRR. abs/1510.07338,
Kantchelian, A., Tschantz M. Carl, Afroz S., Miller B., Shankar V., Bachwani R., et al. (2015).  Better Malware Ground Truth: Techniques for Weighting Anti-Virus Vendor Labels. Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security. 45–56.
Vallina-Rodriguez, N., Sundaresan S., Kreibich C., Weaver N., & Paxson V. (2015).  Beyond the Radio: Illuminating the Higher Layers of Mobile Networks.
Fifield, D., Lan C., Hynes R., Wegmann P., & Paxson V. (2015).  Blocking-resistant communication through domain fronting. Proceedings of the Privacy Enhancing Technologies Symposium (PETS).
Fornasa, M., Stecca M., Maresca M., & Baglietto P. (2015).  Bounded Latency Spanning Tree Reconfiguration. Computer Networks. 76, 259-274.
Akkus, I. Ekin, & Weaver N. (2015).  The Case for a General and Interaction-Based Third-Party Cookie Policy.
Afroz, S., Fifield D., Tschantz M. Carl, Paxson V., & Tygar J.D.. (2015).  Censorship Arms Race: Research vs. Practice. Proceedings of the Workshop on Hot Topics in Privacy Enhancing Technologies (HotPETs).
Hasan, S., Ben-David Y., Bittman M., & Raghavan B. (2015).  The Challenges of Scaling WISPs.
Marczak, B., Weaver N., Dalek J., Fifield D., McKune S., Rey A., et al. (2015).  China’s Great Cannon. The Citizen Report.
Pathak, D., Krahenbuhl P., & Darrell T. (2015).  Constrained Convolutional Neural Networks for Weakly Supervised Segmentation. The IEEE International Conference on Computer Vision (ICCV). 1796-1804.
Pathak, D., Kraehenbuehl P., Yu S. X., & Darrell T. (2015).  Constrained Structured Regression with Convolutional Neural Networks. CoRR. abs/1511.07497,
Friedland, G., Janin A., Lei H., Choi J., & Sommer R. (2015).  Content-Based Privacy for Consumer-Produced Multimedia. 157-173.
Zheng, X., Jiang J., Liang J., Duan H., Chen S.., Wan T., et al. (2015).  Cookies Lack Integrity: Real-World Implications. 707-721.
Krahenbuhl, P., Doersch C., Donahue J., & Darrell T. (2015).  Data-dependent Initializations of Convolutional Neural Networks. CoRR. abs/1511.06856,
Rohrbach, A., Rohrbach M., Tandon N., & Schiele B. (2015).  A Dataset for Movie Description.
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.
McGillivary, P.., Stecca M., Maresca M., & Baglietto P. (2015).  Designing New Arctic Ships to Incorporate Cloud Computing for Improved Information Systems and Vessel Management.
Hoffman, J., Pathak D., Darrell T., & Saenko K. (2015).  Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2883-2891.
Narihira, T., Maire M., & Yu S. X. (2015).  Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression. Proceedings of International Conference on Computer Vision.

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