Data-driven Science - 2019

Kloster, K., Poel, A., & Sullivan, B. D. (2019). Mining maximal induced bicliques using odd cycle transversals. SIAM International Conference on Data Mining, SDM 2019, 324–332. https://doi.org/10.1137/1.9781611975673.37

Lavallee, B., Russell, H., Sullivan, B. D., & Poel, A. (2019). Approximating vertex cover using structural rounding. ArXiv. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85094768942&partnerID=MN8TOARS

Oh, C., Zheng, Z., Shen, X., Zhai, J., & Yi, Y. (2019). POSTER: GOPipe: A Granularity-Oblivious Programming Framework for Pipelined Stencil Executions on GPU. PROCEEDINGS OF THE 24TH SYMPOSIUM ON PRINCIPLES AND PRACTICE OF PARALLEL PROGRAMMING (PPOPP '19), pp. 431–432. https://doi.org/10.1145/3293883.3301494

Sullivan, B. D., Poel, A., & Woodlief, T. (2019). Faster Biclique Mining in Near-Bipartite Graphs. ANALYSIS OF EXPERIMENTAL ALGORITHMS, SEA2 2019, Vol. 11544, pp. 424–453. https://doi.org/10.1007/978-3-030-34029-2_28

Demaine, E. D., Goodrich, T. D., Kloster, K., Lavallee, B., Liu, Q. C., Sullivan, B. D., … Poel, A. (2019). Structural Rounding: Approximation Algorithms for Graphs Near an Algorithmically Tractable Class. 27TH ANNUAL EUROPEAN SYMPOSIUM ON ALGORITHMS (ESA 2019), Vol. 144. https://doi.org/10.4230/LIPIcs.ESA.2019.37

Jones, J. L., Broughton, R., Iamsasri, T., Fancher, C. M., Wilson, A. G., Reich, B., & Smith, R. C. (2019). The use of Bayesian inference in the characterization of materials and thin films. ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES, Vol. 75, pp. A211–A211. https://doi.org/10.1107/S0108767319097940

Guan, H., Ning, L., Lin, Z., Shen, X., Zhou, H., & Lim, S.-H. (2019). In-Place Zero-Space Memory Protection for CNN. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, & R. Garnett (Eds.), Advances in Neural Information Processing Systems Proceedings.

Zheng, Z., Oh, C., Zhai, J., Shen, X., Yi, Y., & Chen, W. (2019). HiWayLib. Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS '19. Presented at the the Twenty-Fourth International Conference. https://doi.org/10.1145/3297858.3304032

Guan, H., Shen, X., & Lim, S.-H. (2019). Wootz: a compiler-based framework for fast CNN pruning via composability. Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation  - PLDI 2019. Presented at the the 40th ACM SIGPLAN Conference. https://doi.org/10.1145/3314221.3314652

Li, X., Zhang, L., & Shen, X. (2019). IA-graph based inter-app conflicts detection in open IoT systems. Proceedings of the 20th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems  - LCTES 2019. Presented at the the 20th ACM SIGPLAN/SIGBED International Conference. https://doi.org/10.1145/3316482.3326350

Ning, L., & Shen, X. (2019). Deep reuse. Proceedings of the ACM International Conference on Supercomputing  - ICS '19. Presented at the the ACM International Conference. https://doi.org/10.1145/3330345.3330384

Yang, S., Shen, X., & Chi, M. (2019). Streamline Density Peak Clustering for Practical Adoptions. Proceedings of the 28th ACM International Conference on Information and Knowledge Management  - CIKM '19. Presented at the the 28th ACM International Conference. https://doi.org/10.1145/3357384.3358053

Agrawal, A., Fu, W., Chen, D., Shen, X., & Menzies, T. (2019). How to "DODGE" Complex Software Analytics. IEEE Transactions on Software Engineering, 1–1. https://doi.org/10.1109/tse.2019.2945020

Jin, H., Shen, X., Lovas, R., & Liao, X. (2019). Special Issue: Graph Computing. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE. https://doi.org/10.1002/cpe.5452

Typhina, E., & Wilson, A. (2019). Discussion on “Effective interdisciplinary collaboration between statisticians and other subject matter experts.” Quality Engineering. https://doi.org/10.1080/08982112.2018.1539233

Tian, Y., Bondell, H. D., & Wilson, A. (2019). Bayesian variable selection for logistic regression. STATISTICAL ANALYSIS AND DATA MINING, 12(5), 378–393. https://doi.org/10.1002/sam.11428

Ning, L., Guan, H., & Shen, X. (2019). Adaptive Deep Reuse: Accelerating CNN Training on the Fly. 2019 IEEE 35TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2019), pp. 1538–1549. https://doi.org/10.1109/ICDE.2019.00138

Gasior, K., Wagner, N. J., Cores, J., Caspar, R., Wilson, A., Bhattacharya, S., & Hauck, M. L. (2019). The role of cellular contact and TGF-beta signaling in the activation of the epithelial mesenchymal transition (EMT). CELL ADHESION & MIGRATION, 13(1), 63–75. https://doi.org/10.1080/19336918.2018.1526597

Demaine, E. D., Reidl, F., Rossmanith, P., Villaamil, F. S., Sikdar, S., & Sullivan, B. D. (2019). Structural sparsity of complex networks: Bounded expansion in random models and real-world graphs. Journal of Computer and System Sciences, 105, 199–241. https://doi.org/10.1016/j.jcss.2019.05.004

Gilman, J. F., Fronczyk, K. M., & Wilson, A. G. (2019). Bayesian modeling and test planning for multiphase reliability assessment. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 35(3), 750–760. https://doi.org/10.1002/qre.2406

Horton, E., Kloster, K., & Sullivan, B. D. (2019). Subgraph centrality and walk-regularity. Linear Algebra and Its Applications, 570, 225–244. https://doi.org/10.1016/j.laa.2019.02.005