Publikationer

Søg publikationer fra Institut for Datalogi

Liste over publikationer af videnskabelige medarbejdere fra Institut for Datalogi, Aarhus Universitet.

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Zottarel, A. (2013). Public key cryptography from weaker assumptions. Institut for Datalogi, Aarhus Universitet.

Zizzo, A. R., Hvidman, L., Salvig, J. D., Holst, L., Kyng, M. & Petersen, O. B. (2022). Home management by remote self-monitoring in intermediate- and high-risk pregnancies: A retrospective study of 400 consecutive women. Acta Obstetricia et Gynecologica Scandinavica, 101(1), 135-144. https://doi.org/10.1111/aogs.14294

Zimek, A., Assent, I. & Vreeken , J. (2014). Frequent Pattern Mining Algorithms for Data Clustering. I C. C. Aggarwal & J. Han (red.), Frequent Pattern Mining (s. 403-423). Springer. https://doi.org/10.1007/978-3-319-07821-2_16

Zhu, F., Zhang, Z. & Qu, Q. (2013). A direct mining approach to efficient constrained graph pattern discovery. Association for Computing Machinery. Special Interest Group on Management of Data. International Conference Proceedings, 821-832. https://doi.org/10.1145/2463676.2463723

Zhu, Y., Honnet, C., Kang, Y., Zhu, J., Zheng, A. J., Heinz, K., Tang, G., Musk, L., Wessely, M. & Mueller, S. (2023). Demonstration of ChromoCloth: Re-Programmable Multi-Color Textures through Flexible and Portable Light Source. I UIST 2023 Adjunct - Adjunct Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology Artikel 73 Association for Computing Machinery. https://doi.org/10.1145/3586182.3615811

Zhong, Z. & Mottin, D. (2023). Knowledge-augmented Graph Machine Learning for Drug Discovery: From Precision to Interpretability. I KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (s. 5841-5842). Association for Computing Machinery, Inc.. https://doi.org/10.1145/3580305.3599563

Zhong, Z., Jiang, Y. & Mottin, D. (2022). On the Robustness of Post-hoc GNN Explainers to Label Noise. Afhandling præsenteret på Learning on Graphs Conference 2022.

Zhao, Z. & Elmqvist, N. (2023). The Stories We Tell About Data: Surveying Data-Driven Storytelling Using Visualization. IEEE Computer Graphics and Applications, 43(4), 97-110. https://doi.org/10.1109/MCG.2023.3269850

Zhang, Y., Chong, M. K., Müller, J., Bulling, A. & Gellersen, H. (2015). Eye tracking for public displays in the wild. Personal and Ubiquitous Computing, 19(5-6), 967-981. https://doi.org/10.1007/s00779-015-0866-8

Zhang, Y., Li, Y., Tan, T. & Xue, J. (2018). Ripple: Reflection analysis for Android apps in incomplete information environments. Software - Practice and Experience, 48(8), 1419-1437. https://doi.org/10.1002/spe.2577

Zhang, K., Zhou, J., Tao, D., Karras, P., Li, Q. & Xiong, H. (2020). Geodemographic Influence Maximization. I KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (s. 2764-2774). Association for Computing Machinery. https://doi.org/10.1145/3394486.3403327

Zerny, I. (2013). On Graph Rewriting, Reduction, and Evaluation in the Presence of Cycles. Higher-Order and Symbolic Computation, 26(1), 63–84. https://doi.org/10.1007/s10990-014-9103-9

Zerny, I. (2014). The interpretation and inter-derivation of small-step and big-step specifications. Department of Computer Science, University of Aarhus.

Zerny, I. & Danvy, O. (2013). A synthetic operational account of call-by-need evaluation. I R. Peña & T. Schrijvers (red.), Proceedings of the 15th Symposium on Principles and Practice of Declarative Programming, PPDP '13 (s. 97-108). Association for Computing Machinery. https://doi.org/10.1145/2505879.2505898

Zengfeng, H., Ke, Y. & Zhang, Q. (2012). Randomized algorithms for tracking distributed count, frequencies, and ranks. I K. Markus , B. Michael & L. Maurizio (red.), PODS '12 Proceedings of the 31st symposium on Principles of Database Systems (s. 295-306 ). Association for Computing Machinery. https://doi.org/10.1145/2213556.2213596

Zardbani, F., Afshani, P. & Karras, P. (2020). Revisiting the theory and practice of database cracking. I A. Bonifati, Y. Zhou, M. A. Vaz Salles, A. Bohm, D. Olteanu, G. Fletcher, A. Khan & B. Yang (red.), Advances in Database Technology - EDBT 2020: 23rd International Conference on Extending Database Technology, Proceedings (s. 415-418). openproceedings.org. https://doi.org/10.5441/002/edbt.2020.46

Zardbani, F., Mamoulis, N., Idreos, S. & Karras, P. (2023). Adaptive Indexing of Objects with Spatial Extent. Proceedings of the VLDB Endowment, 16(9), 2248-2260. https://doi.org/10.14778/3598581.3598596

Zakarias, S. N. H. (2014). Secure Computation in the Preprocessing Model. Department of Computer Science, Aarhus University.

Zakarias, R. W. & Damgård, I. B. (2015). Fast Oblivious AES A Dedicated application of the MiniMac protocol. https://eprint.iacr.org/2015/989.pdf

Zakarias, R. W. (2016). Practical Secure Computation with Pre-Processing. Department of Computer Science, Aarhus University.

Zagermann, J., Pfeil, U., Rädle, R., Jetter, H.-C., Klokmose, C. N. & Reiterer, H. (2016). When Tablets meet Tabletops: The Effect of Tabletop Size on Around-the-Table Collaboration with Personal Tablets. I CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (s. 5470-5481). Association for Computing Machinery. https://doi.org/10.1145/2858036.2858224

Yiu, M. L., Assent, I. & Jensen, C. S. (2012). Outsourced Similarity Search on Metric Data Assets. I E E E Transactions on Knowledge & Data Engineering, 24(2), 338-352. https://doi.org/10.1109/TKDE.2010.222

Yiu, M. L., Jensen, C. S., Møller, J. & Lu, H. (2011). Design and analysis of a ranking approach to private location-based services. A C M Transactions on Database Systems, 36(2), Article 10, p.1 - 42. https://doi.org/10.1145/1966385.1966388

Yi, K. & Zhang, Q. (2013). Optimal Tracking of Distributed Heavy Hitters and Quantiles. Algorithmica, 65(1), 206-223 . https://doi.org/10.1007/s00453-011-9584-4

Yi, K., Wang, L. & Wei, Z. (2014). Indexing for summary queries: Theory and practice. A C M Transactions on Database Systems, 39(1), Artikel 2. https://doi.org/10.1145/2508702

Yang, B., Fantini, E. N. & Jensen, C. S. (2013). iPark: Identifying Parking Spaces from Trajectories. I G. Guerrini & N. W. Paton (red.), Proceedings of The 16th International Conference on Extending Database Technology: EDBT 2013 (s. 705-708 ). Association for Computing Machinery. https://doi.org/10.1145/2452376.2452459

Yang, B., Kaul, M. & Jensen, C. S. (2014). Using Incomplete Information for Complete Weight Annotation of Road Networks. I E E E Transactions on Knowledge & Data Engineering, 26(5), 1267-1279. https://doi.org/10.1109/TKDE.2013.89

Yang, B., Guo, C., Jensen, C. S., Kaul, M. & Shang, S. (2014). Stochastic skyline route planning under time-varying uncertainty. I 2014 IEEE 30th International Conference on Data Engineering (ICDE), (s. 136-147). IEEE. https://doi.org/10.1109/ICDE.2014.6816646

Yang, J. (2015). Efficient Algorithms for HandlingMassive Terrains. Department of Computer Science, University of Aarhus.

Yang, B., Guo, C., Ma, Y. & Jensen, C. S. (2015). Toward personalized, context-aware routing. V L D B Journal, 24(2), 297-318. https://doi.org/10.1007/s00778-015-0378-1

Yang, B., Guo, C. & Jensen, C. S. (2013). Travel cost inference from sparse, spatio-temporally correlated time series using markov models. Proceedings of the VLDB Endowment, 6(9), 769-780. http://dl.acm.org/citation.cfm?id=2536360.2536375&coll=DL&dl=ACM&CFID=383343957&CFTOKEN=67321284

Yang, Y., Li, Y., Karras, P. & Tung, A. K. H. (2021). Context-aware Outstanding Fact Mining from Knowledge Graphs. I KDD 2021 - Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (s. 2006-2016). Association for Computing Machinery. https://doi.org/10.1145/3447548.3467272

Yamasaki, S., Sasaki, Y., Karras, P. & Onizuka, M. (2023). Holistic Prediction on a Time-Evolving Attributed Graph. Proceedings of the Annual Meeting of the Association for Computational Linguistics, 61(1), 13676-13694. https://doi.org/10.18653/v1/2023.acl-long.765

Yalçin, M. A., Elmqvist, N. & Bederson, B. B. (2016). Cognitive stages in visual data exploration. I M. Sedlmair, H. Lam, P. Isenberg, T. Isenberg & N. Mahyar (red.), Proceedings - Beyond Time and Errors: Novel Evaluation Methods for Visualization, BELIV 2016 - 6th Bi-Annual Workshop (s. 86-95). Association for Computing Machinery, Inc.. https://doi.org/10.1145/2993901.2993902

Yakoubov, S. (2020). Universally Composable Accumulators.

Yakoubov, S., Kolby, S., Canetti, R., Soria Vazquez, E. & Ravi, D. (2023). Taming Adaptivity in YOSO Protocols: The Modular Way. I Theory of Cryptography (TCC)

Yakoubov, S., Ravi, D. & Melissaris Papanikolaou, N. (2023). Threshold-Optimal MPC with Friends and Foes. I Indocrypt

Xue, H., Kelmann, P., Inati, S., Sørensen, T. S. & Hansen, M. (2014). 3D High Resolution l1-SPIRiT Reconstruction on Gadgetron based Cloud: no. 1882. Abstract fra Joint Annual Meeting ISMRM-ESMRMB, Milan, Italien. http://www.ismrm.org/14/

Xue, H., Kelmann, P., Inati, S., Sørensen, T. S. & Hansen, M. (2014). Distributed Computing on Gadgetron: A new paradigm for MRI reconstruction: no. 1579. Poster session præsenteret på Joint Annual Meeting Ismrm-Esmrmb, Milan, Italien. http://www.ismrm.org/14/program_files/TP05.htm

Xue, H., Inati, S., Sangild, T., Kellman, P. & Hansen, M. (2015). Distributed MRI Reconstruction using Gadgetron based Cloud Computing. Magnetic Resonance in Medicine, 73(3), 1015–1025. https://doi.org/10.1002/mrm.25213

Xu, Y., Johnson, P. M., Moore, C. A., Brewer, R. S. & Takayama, J. (2013). SGSEAM: Assessing serious game frameworks from a stakeholder experience perspective. I Gamification 2013: Proceedings of the First International Conference on Gameful Design, Research, and Applications Enterprice Gamification Consultancy. http://csdl.ics.hawaii.edu/techreports/2013/13-03/13-03.pdf

Xu, Y., Johnson, P. M., Lee, G. E., Moore, C. A. & Brewer, R. S. (2014). Makahiki: An open source serious game framework for sustainability education and conservation. I P. Kommers, T. Issa, T. Issa, D.-F. Chang & P. Isaías (red.), International Conference on Sustainability, Technology, and Education, STE 2014: proceedings (s. 131-138). International Association for Development, IADIS. http://www.iadisportal.org/digital-library/makahiki-an-open-source-serious-game-framework-for-sustainability-education-and-conservation

Wüstenberg, M., Blunck, H., Grønbæk, K. & Kjærgaard, M. B. (2014). Distinguishing Electric Vehicles from Fossil-Fueled Vehicles with Mobile Sensing. I M. Gabor & R. Zhang (red.), 15th IEEE International Conference on Mobile Data Management (MDM): Proceedings (s. 211 - 220 (vol.1)). IEEE. https://doi.org/10.1109/MDM.2014.32

Wu, D., Yiu, M. L., Jensen, C. S. & Cong, G. (2011). Efficient continuously moving top-k spatial keyword query processing. Proceedings of the International Conference on Data Engineering, 541-552. https://doi.org/10.1109/ICDE.2011.5767861

Wu, D., Yiu, M. L., Cong, G. & Jensen, C. S. (2012). Joint Top-K Spatial Keyword Query Processing. I E E E Transactions on Knowledge & Data Engineering, 24(10), 1889 - 1903 . https://doi.org/10.1109/TKDE.2011.172

Wu, D., Cong, G. & Jensen, C. S. (2012). A framework for efficient spatial web object retrieval. V L D B Journal, 21(6), 797-822 . https://doi.org/10.1007/s00778-012-0271-0

Wu, D., Yiu, M. L. & Jensen, C. S. (2013). Moving Spatial Keyword Queries: Formulation, Methods, and Analysis. A C M Transactions on Database Systems, 38(1), Artikel 7. https://doi.org/10.1145/2445583.2445590

Wu, S., Hou U, L. & Karras, P. (2023). k-Best Egalitarian Stable Marriages for Task Assignment. Proceedings of the VLDB Endowment, 16(11), 3240-3252. https://doi.org/10.14778/3611479.3611522

Wriedt Larsen, R., Obel, C., Skovgård Jensen, T. & Grønbæk, K. (2014). Big data giver gladere børn og bedre busruter. Videnskab.dk [online].

Woodruff, D. P. & Zhang, Q. (2011). Tight Bounds for Distributed Functional Monitoring. http://arxiv.org/abs/1112.5153

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