Publications

Afshani, P., Killmann, R. & Larsen, K. G. (2022). Hierarchical Categories in Colored Searching. In S. W. Bae & H. Park (Eds.), 33rd International Symposium on Algorithms and Computation, ISAAC 2022 Article 25 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ISAAC.2022.25

Larsen, K. G. (2012). Higher Cell Probe Lower Bounds for Evaluating Polynomials. In FOCS'12: IEEE 53rd Annual Symposium on Foundations of Computer Science (pp. 293 - 301 ). IEEE Computer Society Press. https://doi.org/10.1109/FOCS.2012.21

Arge, L., Afshani, P. & Larsen, K. G. (2012). Higher-dimensional Orthogonal Range Reporting and Rectangle Stabbing in the Pointer Machine Model. In Proceedings of the 2012 Symposuim on Computational Geometry (pp. 323-338). Association for Computing Machinery. https://doi.org/10.1145/2261250.2261299

Moeslund, J. E., Andersen, D. K., Brunbjerg, A. K., Bruun, H. H., Fløjgaard, C., McQueen, S. N., Nygaard, B. & Ejrnæs, R. (2023). High nutrient loads hinder successful restoration of natural habitats in freshwater wetlands. Restoration Ecology, 31(7), Article e13796. https://doi.org/10.1111/rec.13796

Alamdari, S., Angelini, P., Barrera-Cruz, F., Chan, T. M., Da Lozzo, G., Di Battista, G., Frati, F., Haxell, P., Lubiw, A., Patrignani, M., Roselli, V., Singla, S. & Wilkinson, B. T. (2017). How to Morph Planar Graph Drawings. S I A M Journal on Computing, 46(2), 824-852. https://doi.org/10.1137/16M1069171

Baum, C., Damgård, I. B., Larsen, K. G. & Nielsen, M. (2016). How to prove knowledge of small secrets. In J. Katz & M. Robshaw (Eds.), Advances in Cryptology - 36th Annual International Cryptology Conference, CRYPTO 2016, Proceedings: CRYPTO 2016: Advances in Cryptology – CRYPTO 2016 (Vol. 9816, pp. 478-498). Springer VS. https://doi.org/10.1007/978-3-662-53015-3_17

Odgaard, M. V., Moeslund, J. E., Dalgaard, T., Bøcher, P. K. & Svenning, J-C. (2014). Human-driven topographic effects on the distribution of forest in a flat, lowland agricultural region. Journal of Geographical Sciences, 24(1), 76-92. https://doi.org/10.1007/s11442-014-1074-6

Moeslund, J. E., Bøcher, P. K., Svenning, J-C., Møllehave, T. & Arge, L. (2009). Impacts of 21^stcentury sea-level rise on a Danish major city - an assessment based on fine-resolution digital topography and a new flooding algorithm. IOP Conference Series: Earth and Environment Science, 8(1), 012022. https://doi.org/10.1088/1755-1315/8/1/012022

Brodal, G. S. & Srinivasan, V. (2000). Improved Bounds for Dictionary Look-up with One Error. Information Processing Letters, 75(1-2), 57-59. https://doi.org/10.1016/S0020-0190(00)00079-X

Brodal, G. S., Arge, L. & Georgiadis, L. (2006). Improved Dynamic Planar Point Location. In Proceedings of the 47th Annual Symposium on Foundations of Computer Science (pp. 305-314). IEEE. https://doi.org/10.1109/FOCS.2006.40

Afshani, P. (2012). Improved pointer machine and I/O lower bounds for simplex range reporting and related problems. In Proceedings of the 2012 Symposuim on Computational Geometry, SoCG (pp. 339-346 ). Association for Computing Machinery. https://doi.org/10.1145/2261250.2261301

Larsen, K. G. & Nguyen, H. L. (2012). Improved Range Searching Lower Bounds. In Proceedings of the 2012 symposuim on Computational Geometry: Chapel Hill, NC, USA — June 17 - 20, 2012 (pp. 171-178). Association for Computing Machinery. https://doi.org/10.1145/2261250.2261275

Afshani, P. & Phillips, J. M. (2019). Independent range sampling, revisited again. In G. Barequet & Y. Wang (Eds.), 35th International Symposium on Computational Geometry, SoCG 2019 Article 4 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.SoCG.2019.4

Moeslund, J. E. & Helsing, F., (2020). Indsamlingsforbud for danske dagsommerfugle, 13 p., Notat fra DCE - Nationalt Center for Miljø og Energi Vol. 2020 No. 24 https://dce.au.dk/fileadmin/dce.au.dk/Udgivelser/Notatet_2020/N2020_24.pdf

Madalgo, P. A., Barbay, J. & Chan, T. M. (2017). Instance-optimal geometric algorithms. Journal of the ACM, 64(1), Article 3. https://doi.org/10.1145/3046673

Brodal, G. S., Greve, M., Pandy, V. & Satti, S. R. (2014). Integer representations towards efficient counting in the bit probe model. Journal of Discrete Algorithms, 26(May), 34–44. https://doi.org/10.1016/j.jda.2013.11.001

Brodal, G. S., Greve, M., Pandey, V. & Satti, S. R. (2011). Integer Representations towards Efficient Counting in the Bit Probe Model. Lecture Notes in Computer Science, 6648, 206-217. https://doi.org/10.1007/978-3-642-20877-5_22

Kejlberg-Rasmussen, C., Tao, Y., Tsakalidis, K., Tsichlas, K. & Yoon, J. (2021). I/O-efficient 2-d orthogonal range skyline and attrition priority queues. Computational Geometry: Theory and Applications, 93, Article 101689. https://doi.org/10.1016/j.comgeo.2020.101689

Larsen, K. G. & Pagh, R. (2012). I/O-Efficient Data Structures for Colored Range and Prefix Reporting. The Annual A C M - S I A M Symposium on Discrete Algorithms. Proceedings, 23, 583-592. http://siam.omnibooksonline.com/2012SODA/index.html

Kejlberg-Rasmussen, C., Tsakalidis, K. & Tsichlas, K. (2012). I/O-Efficient Dynamic Planar Range Skyline Queries. arXiv.org. http://arxiv.org/abs/1207.2341

Agarwal, P. K., Arge, L. A., Brodal, G. S. & Vitter, J. S. (1999). I/O-efficient dynamic point location in monotone planar subdivisions. In Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms (pp. 11-20). Association for Computing Machinery.

Afshani, P., Arge, L. A. & Larsen, K. D. (2010). I/O-efficient Orthogonal Range Reporting in Three and Higher Dimensions. Abstract from Workshop on Massive Data Algorithms, Snowbird, United States.

Kejlberg-Rasmussen, C., Tao, Y., Tsakalidis, K., Tsichlas, K. & Yoon, J. (2013). I/O-Efficient Planar Range Skyline and Attrition Priority Queues. In R. Hull & W. Fan (Eds.), Proceedings of the 32nd symposium on Principles of database systems , PODS '13 (pp. 103-114 ). Association for Computing Machinery. https://doi.org/10.1145/2463664.2465225

Afshani, P. & Sitchinava, N. (2014). I/O-efficient range minima queries. In R. Ravi & I. L. Gørtz (Eds.), Algorithm Theory – SWAT 2014: 14th Scandinavian Symposium and Workshops, Copenhagen, Denmark, July 2-4, 2014. Proceedings (pp. 1-12). Springer VS. https://doi.org/10.1007/978-3-319-08404-6_1

Arge, L. & Larsen, K. G. (2012). I/O-Efficient Spatial Data Structures for Range Queries. SIGSPATIAL Special, 4(2), 2-7. http://www.sigspatial.org/sigspatial-special-issues/SIGSPATIALSpecialVol4No2.pdf

Moeslund, J. E., Arge, L., Bøcher, P. K., Nygaard, B. & Svenning, J-C. (2009). Konsekvenser af "coastal squeezing" for plantesamfund på strandenge i Danmark.

Moeslund, J. E., (2021). Kortlægning af beskyttede dagsommerfugle ved Natura 2000-område: Bygholm Ådal, 5 p., Fagligt notat fra DCE – Nationalt Center for Miljø og Energi Vol. 2021 No. 22 https://dce.au.dk/fileadmin/dce.au.dk/Udgivelser/Notater_2021/N2021_22.pdf

Moeslund, J. E., Zlinszky, A., Ejrnæs, R., Brunbjerg, A. K., Bøcher, P. K., Svenning, J. C. & Normand, S. (2019). Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent. Ecological Applications, 29(5), Article e01907. https://doi.org/10.1002/eap.1907

Chan, T. M., Durocher, S., Skala, M. & Wilkinson, B. T. (2012). Linear-Space Data Structures for Range Minority Query in Arrays.

Chan, T. M., Durocher, S., Skala, M. & Wilkinson, B. T. (2015). Linear-Space Data Structures for Range Minority Query in Arrays. Algorithmica, 72(4), 901-913. https://doi.org/10.1007/s00453-014-9881-9

Chan, T. M., Durocher, S., Larsen, K. G., Morrison, J. & Wilkinson, B. T. (2012). Linear-Space Data Structures for Range Mode Query in Arrays. Leibniz International Proceedings in Informatics, 14, 290-301. https://doi.org/10.4230/LIPIcs.STACS.2012.290

Chan, T. M., Durocher, S., Larsen, K. G., Morrison, J. & Wilkinson, B. T. (2014). Linear-Space Data Structures for Range Mode Query in Arrays. Theory of Computing Systems, 55(4), 719-741. https://doi.org/10.1007/s00224-013-9455-2

Afshani, P., Iacono, J., Jayapaul, V., Karsin, B. & Sitchinava , N. (2022). Locality-of-Reference Optimality of Cache-Oblivious Algorithms. In 3rd Symposium on Algorithmic Principles of Computer Systems, (APOCS) (pp. 31 - 45). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611977059.3

Brodal, G. S., Fagerberg, R. & Farach-Colton, M. (Ed.) (2003). Lower Bounds for External Memory Dictionaries. In Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms (pp. 546-554). Society for Industrial and Applied Mathematics.

Farhadi, A., Hajiaghayi, M. T., Larsen, K. G. & Shi, E. (2019). Lower bounds for external memory integer sorting via network coding. In M. Charikar & E. Cohen (Eds.), STOC 2019 - Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing (pp. 997-1008). Association for Computing Machinery. https://doi.org/10.1145/3313276.3316337

Afshani, P. & Cheng, P. (2023). Lower Bounds for Intersection Reporting Among Flat Objects. In E. W. Chambers & J. Gudmundsson (Eds.), 39th International Symposium on Computational Geometry, SoCG 2023 Article 3 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.SoCG.2023.3

Afshani, P., Freksen, C. B., Kamma, L. & Larsen, K. G. (2019). Lower bounds for multiplication via network coding. Leibniz International Proceedings in Informatics, LIPIcs, 132, Article 10. https://doi.org/10.4230/LIPIcs.ICALP.2019.10

Larsen, K. G., Simkin, M. & Yeo, K. (2020). Lower Bounds for Multi-server Oblivious RAMs. In R. Pass & K. Pietrzak (Eds.), Theory of Cryptography - 18th International Conference, TCC 2020, Proceedings (pp. 486-503). Springer. https://doi.org/10.1007/978-3-030-64375-1_17

Jacob, R., Larsen, K. G. & Nielsen, J. B. (2019). Lower Bounds for Oblivious Data Structures. In T. M. Chan (Ed.), Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 2439-2447). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611975482.149

Larsen, K. G., Malkin, T., Weinstein, O. & Yeo, K. (2020). Lower Bounds for Oblivious Near-Neighbor Search. In S. Chawla (Ed.), SODA '20: Proceedings of the Thirty-First Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 1116-1134). Society for Industrial and Applied Mathematics. https://doi.org/10.5555/3381089.3381157

Afshani, P. & Cheng, P. (2021). Lower bounds for semialgebraic range searching and stabbing problems. In K. Buchin & E. C. de Verdiere (Eds.), 37th International Symposium on Computational Geometry, SoCG 2021 Article 8 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.SoCG.2021.8

Afshani, P. & Cheng, P. (2023). Lower Bounds for Semialgebraic Range Searching and Stabbing Problems. Journal of the ACM, 70(2), 1-26. Article 16. https://doi.org/10.1145/3578574

Afshani, P. & Zeh, N. (2012). Lower Bounds for Sorted Geometric Queries in the I/O Model. Lecture Notes in Computer Science, 7501, 48-59 . https://doi.org/10.1007/978-3-642-33090-2_6

Moeslund, J. E., Ejrnæs, R. & Wind, P. (2015). Manual til rødlistevurdering af danske arter 2013-2019. Aarhus Universitet, DCE – Nationalt Center for Miljø og Energi ©. Teknisk rapport fra DCE - Nationalt Center for Miljø og Energi No. 54

Moeslund, J. E., Nygaard, B. & Ejrnæs, R. (2020). Manual til rødlistevurdering af danske arter 2020-2030. Aarhus Universitet, DCE - Nationalt Center for Miljø og Energi. Teknisk rapport No. 188 https://dce2.au.dk/pub/tr188.pdf

Večeřa, M., Axmanova, I., Padullés Cubino, J., Lososová, Z., Divíšek, J., Knollová, I., Aćić, S., Biurrun, I., Boch, S., Bonari, G., Antonio Campos, J., Čarni, A., Carranza, M. L., Casella, L., Chiarucci, A., Ćušterevska, R., Pauline, D., Dengler, J., Fernandez-Gonzalez, F. ... Chytrý, M. (2021). Mapping species richness of plant families in European vegetation. Journal of Vegetation Science, 32(3), Article e13035. https://doi.org/10.1111/jvs.13035

Grønlund, A., Kamma, L., Larsen, K. G., Mathiasen, A. & Nelson, J. (2019). Margin-Based Generalization Lower Bounds for Boosted Classifiers. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox & R. Garnett (Eds.), Advances in Neural Information Processing Systems 32 (NIPS 2019) (Vol. 32). Neural Information Processing Systems Foundation. https://arxiv.org/abs/1909.12518

Grønlund, A., Kamma, L. & Larsen, K. G. (2020). Margins are Insufficient for Explaining Gradient Boosting. In H. Larochelle, MA. Ranzato, R. Hadsell, M-F. Balcan & H-T. Lin (Eds.), Advances in Neural Information Processing Systems 33 (NeurIPS 2020) https://proceedings.neurips.cc/paper/2020/hash/146f7dd4c91bc9d80cf4458ad6d6cd1b-Abstract.html

Caspersen, M. E., Bennedsen, J. & Larsen, K. D. (2007). Mental Models and Programming Aptitude. S I G C S E Bulletin Inroads, 39(3), 206-210. https://doi.org/10.1145/1269900.1268845

Larsen, K. G. (2013). Models and Techniques for Proving Data Structure Lower Bounds. Department of Computer Science, Aarhus University.

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