Publications

Found 281 results
Author Title Type [ Year(Asc)]
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2019
Callejo, P., Cuevas R., Vallina-Rodriguez N., & Cuevas A. (2019).  Measuring the Global Recursive DNS Infrastructure: A View From the Edge. IEEE Access.
Derezinski, M.., Clarkson K.. L., Mahoney M. W., & Warmuth M.. K. (2019).  Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression. Proceedings of 2019 COLT.
Simsek, M., Hößler T., Jorswieck E., Klessig H., & Fettweis G. (2019).  Multiconnectivity in Multicellular, Multiuser Systems: A Matching- Based Approach. Proceedings of the IEEE. 107(2), 394-413.
2018
Mahoney, M. W., Duchi J. C., & Gilbert A. C. (2018).  The Mathematics of Data. 25,
Taber, A., Kumar G., Freytag M., & Shapiro V. (2018).  A moment-vector approach to interoperable analysis. Computer-Aided Design. 102, 139-147.
Iyer, A. Pamanabha, Panda A., Chowdhury M., Akella A., Shenker S., & Stoica I. (2018).  Monarch: Gaining Command on Geo-Distributed Graph Analytics.. Proceedings of HotCloud 2018.
Torrent, T. Timponi, Ellsworth M., Baker C. F., & Matos E. Edison da (2018).  The Multilingual FrameNet Shared Annotation Task: a Preliminary Report.
Liu, X., & Shapiro V. (2018).  Multiscale shape–material modeling by composition. Computer-Aided Design. 102, 194-203.
2017
Amann, J., Gasser O., Scheitle Q., Brent L., Carle G., & Holz R. (2017).  Mission Accomplished? HTTPS Security after DigiNotar. Proceedings of the IMC 2017.
Ousterhout, K., Canel C., Ratnasamy S., & Shenker S. (2017).  Monotasks: Architecting for Performance Clarity in Data Analytics Frameworks. Proceedings of the 26th Symposium on Operating Systems Principles SOSP '17.
Ke, T-W., Yu S. X., & Whitney D. (2017).  Mooney Face Classification and Prediction by Learning across Tone. Proceedings of the International Conference on Image Processing 2017.
Ke, T-W., Yu S. X., & Whitney D. (2017).  Mooney Faces from Photos. Proceedings of the Vision Sciences Society Annual Meeting.
2016
Lawlor, D., Budavári T., & Mahoney M. W. (2016).  Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxy Data. The Astrophysical Journal.
Gittens, A., Devarakonda A., Racah E., Ringenburg M., Gerhardt L., Kottalam J., et al. (2016).  Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.
Zhu, L., Amann J., & Heidemann J. (2016).  Measuring the Latency and Pervasiveness of TLS Certificate Revocation. Proceedings of Passive and Active Measurement Conference (PAM).
Petruck, M. R. L. (2016).  MetaNet, Special Issue of Constructions and Frames: 8.2. 8(2), 
Petruck, M. R. L., & Dodge E. (2016).  MetaNet Tutorial. Proceedings of ACL 2016.
Moskewicz, M. W., Jannesari A., & Keutzer K. (2016).  A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications. arXiv preprint arXiv:1611.06945.
Gleich, D., & Mahoney M. W. (2016).  Mining Large graphs. Handbook of Big Data. 191-220.
Thomee, B., Borth D., & Bernd J. (2016).  Multimedia COMMONS Workshop 2016 (MMCommons'16): Datasets, Evaluation, and Reproducibility. Proceedings of the 2016 ACM Conference on Multimedia (MM '16). 1485-1486.
Friedland, G., Papadopoulos S., Bernd J., & Kompatsiaris Y. (2016).  Multimedia Privacy. Proceedings of the 2016 ACM Conference on Multimedia (MM '16). 1479-1480.
Fukui, A., Park D. Huk, Yang D., Rohrbach A., Darrell T., & Rohrbach M. (2016).  Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding. CoRR. abs/1606.01847,
Richter, P., Wohlfart F., Vallina-Rodriguez N., Allman M., Bush R., Feldmann A., et al. (2016).  A Multi-perspective Analysis of Carrier-Grade NAT Deployment. Proceedings of ACM Internet Measurement Conference.
Gittens, A., Kottalam J., Yang J., Ringenburg M. F., Chhugani J., Racah E., et al. (2016).  A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark. Proceedings of the 5th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics.
2015
Darrell, T., Kloft M., Pontil M., Rätsch G., & Rodner E. (2015).  Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152). Dagstuhl Reports. 5, 18–55.

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