Publications

Høye, T. T., Olsen, K., Moeslund, J. E., Strandberg, M. T. & Kjær, C., (2019). Oversigt og status for de danske sommerfuglearter, 8 p., Notat fra DCE - Nationalt Center for Miljø og Energi (2011-2019) https://dce.au.dk/fileadmin/dce.au.dk/Udgivelser/Notater_2019/Status_danske_sommerfugle.pdf

Moeslund, J. E. & Helsing, F., (2020). Vurdering af WWF’s anbefalinger om at udvide indsamlingsforbud af dagsommerfugle i Danmark, 5 p., Fagligt notat fra DCE – Nationalt Center for Miljø og Energi (2020-...) Vol. 2020 No. 54 https://dce.au.dk/fileadmin/dce.au.dk/Udgivelser/Notatet_2020/N2020_54.pdf

Moeslund, J. E., Nygaard, B. & Ejrnæs, R. (2020). Manual til rødlistevurdering af danske arter 2020-2030. Aarhus University, DCE - Danish Centre for Environment and Energy. Teknisk rapport fra DCE - Nationalt Center for Miljø og Energi Vol. 2020 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

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

Hájek, M., Jimenez-Alfaro, B., Hájek, O., Brancaleoni, L., Cantonati, M., Carbognani, M., Dedić, A., Dítě, D., Gerdol, R., Hájková, P., Horsáková, V., Jansen, F., Kamberović, J., Kapfer, J., Kolari, T. H. M., Lamentowicz, M., Lazarević, P. M., Mašić, E., Moeslund, J. E. ... Biţă-Nicolae, C. (2021). A European map of groundwater pH and calcium. Earth System Science Data, 13(3), 1089-1105. https://doi.org/10.5194/essd-13-1089-2021

Axmanova, I., Kalusová, V., Danihelka, J., Dengler, J., Pergl, J., Pysek, P., Večeřa, M., Attorre, F., Biurrun, I., Boch, S., Conradi, T., Gavilán, R. G., Jimenez-Alfaro, B., Knollová, I., Kuzemko, A., Lenoir, J., Medvecká, J., Moeslund, J. E., Obratov-Petković, D. ... Chytrý, M. (2021). Neophyte invasions in European grasslands. Journal of Vegetation Science, 32(2), Article e12994. https://doi.org/10.1111/jvs.12994

Afshani, P., de Berg, M., Buchin, K., Gao, J., Loffler, M., Nayyeri, A., Raichel, B., Sarkar, R., Wang, H. & Wang, H.-T. (2021). Approximation Algorithms for Multi-Robot Patrol-Scheduling with Min-Max Latency. In S. M. LaValle, M. Lin, T. Ojala, D. Shell & J. Yu (Eds.), Algorithmic Foundations of Robotics XIV-Part A: Proceedings of the Fourteenth Workshop on the Algorithmic Foundations of Robotics (pp. 107-123). Springer. https://doi.org/10.1007/978-3-030-66723-8_7

Afshani, P. (2021). A Lower Bound for Dynamic Fractional Cascading. In ACM-SIAM Symposium on Discrete Algorithms, SODA 2021 (pp. 2229-2248). Association for Computing Machinery. https://doi.org/10.5555/3458064.3458197

Afshani, P. & Cheng, P. (2020). 2D generalization of fractional cascading on axis-aligned planar subdivisions. In Proceedings - 2020 IEEE 61st Annual Symposium on Foundations of Computer Science, FOCS 2020 (pp. 716-727). Article 9317953 IEEE Computer Society Press. https://doi.org/10.1109/FOCS46700.2020.00072

Larsen, K. G., Starup, J. L. & Steensgaard, J. (2021). Further Unifying the Landscape of Cell Probe Lower Bounds. 224-231. Paper presented at Happening virtually , -. https://cs.au.dk/~larsen/papers/FurtherUnifying.pdf

Bury, M., Schwiegelshohn, C. & Sorella, M. (2018). Sketch 'em all: Fast approximate similarity search for dynamic data streams. WSDM 2018 - Proceedings of the 11th ACM International Conference on Web Search and Data Mining, 72-80. https://doi.org/10.1145/3159652.3159694

Bury, M., Grigorescu, E., McGregor, A., Monemizadeh, M., Schwiegelshohn, C., Vorotnikova, S. & Zhou, S. (2019). Structural Results on Matching Estimation with Applications to Streaming. Algorithmica, 81(1), 367-392. https://doi.org/10.1007/s00453-018-0449-y

Barnabo, G., Leonardi, S., Fazzone, A. & Schwiegelshohn, C. (2019). Algorithms for fair team formation in online labour marketplaces. The Web Conference 2019 - Companion of the World Wide Web Conference, WWW 2019, 484-490. https://doi.org/10.1145/3308560.3317587

Becchetti, L., Bury, M., Cohen-Addad, V., Grandoni, F. & Schwiegelshohn, C. (2019). Oblivious dimension reduction for k-means: Beyond subspaces and the Johnson-lindenstrauss lemma. Proceedings of the Annual ACM Symposium on Theory of Computing, 1039-1050. https://doi.org/10.1145/3313276.3316318

Anagnostopoulos, A., Angeletti, F., Arcangeli, F., Schwiegelshohn, C. & Vitaletti, A. (2019). Random projection to preserve patient privacy. CEUR Workshop Proceedings, 2482.

Cohen-Addad, V., Hjuler, N., Parotsidis, N., Saulpic, D. & Schwiegelshohn, C. (2019). Fully dynamic consistent facility location. Advances in Neural Information Processing Systems, 32.

Bury, M., Gentili, M., Schwiegelshohn, C. & Sorella, M. (2021). Polynomial Time Approximation Schemes for All 1-Center Problems on Metric Rational Set Similarities. Algorithmica, 83(5), 1371-1392. https://doi.org/10.1007/s00453-020-00787-3

Munteanu, A., Schwiegelshohn, C., Sohler, C. & Woodruff, D. P. (2019). On coresets for logistic regression. Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI), 267-268. https://doi.org/10.18420/inf2019_37

Schmidt, M., Schwiegelshohn, C. & Sohler, C. (2020). Fair Coresets and Streaming Algorithms for Fair k-means. In E. Bampis & N. Megow (Eds.), Approximation and Online Algorithms - 17th International Workshop, WAOA 2019, Revised Selected Papers (pp. 232-251). Springer. https://doi.org/10.1007/978-3-030-39479-0_16

Munteanu, A. & Schwiegelshohn, C. (2018). Coresets-Methods and History: A Theoreticians Design Pattern for Approximation and Streaming Algorithms. KI - Kunstliche Intelligenz, 32(1), 37-53. https://doi.org/10.1007/s13218-017-0519-3

Jamalabadi, S., Schwiegelshohn, C. & Schwiegelshohn, U. (2020). Commitment and Slack for Online Load Maximization. In Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures (pp. 339–348). Association for Computing Machinery. https://doi.org/10.1145/3350755.3400271

Anagnostopoulos, A., Becchetti, L., Fazzone, A., Menghini, C. & Schwiegelshohn, C. (2020). Spectral Relaxations and Fair Densest Subgraphs. In CIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management (pp. 35–44) https://doi.org/10.1145/3340531.3412036

Bury, M., Schwiegelshohn, C. & Sorella, M. (2020). Similarity Search for Dynamic Data Streams. IEEE Transactions on Knowledge and Data Engineering, 32(11), 2241-2253. https://doi.org/10.1109/TKDE.2019.2916858

Grønlund, A., Kamma, L. & Larsen, K. G. (2020). Near-Tight Margin-Based Generalization Bounds for Support Vector Machines. In H. Daumé III & A. Singh (Eds.), International Conference on Machine Learning (pp. 3737-3746). MLResearch Press. http://proceedings.mlr.press/v119/gronlund20a.html

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

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) (Vol. 2020-December) https://proceedings.neurips.cc/paper/2020/hash/146f7dd4c91bc9d80cf4458ad6d6cd1b-Abstract.html

Larsen, K. G. & Simkin, M. (2020). Secret sharing lower bound: Either reconstruction is hard or shares are long. In C. Galdi & V. Kolesnikov (Eds.), Security and Cryptography for Networks (pp. 566-578). Springer. https://doi.org/10.1007/978-3-030-57990-6_28

Brodal, G. S., Sioutas, S., Tsakalidis, K. & Tsichlas, K. (2020). Fully persistent B-trees. Theoretical Computer Science, 841, 10-26. https://doi.org/10.1016/j.tcs.2020.06.027

Larsen, K. G., Mitzenmacher, M. & Tsourakakis, C. E. (2020). Optimal Learning of Joint Alignments with a Faulty Oracle. In 2020 IEEE International Symposium on Information Theory, ISIT 2020 (pp. 2492-2497). IEEE. https://doi.org/10.1109/ISIT44484.2020.9174310

Valdez, J., Brunbjerg, A. K., Fløjgaard, C., Dalby, L., Clausen, K. K., Pärtel, M., Pfeifer, N., Hollaus, M., Wimmer, M. H., Ejrnæs, R. & Moeslund, J. E. (2021). Relationships between macro-fungal dark diversity and habitat parameters using LiDAR. Fungal Ecology, 51, Article 101054. https://doi.org/10.1016/j.funeco.2021.101054

Fløjgaard, C., Valdez, J. W., Dalby, L., Moeslund, J. E., Clausen, K. K., Ejrnæs, R., Pärtel, M. & Brunbjerg, A. K. (2020). Dark diversity reveals importance of biotic resources and competition for plant diversity across habitats. Ecology and Evolution, 10(12), 6078-6088. https://doi.org/10.1101/685040, https://doi.org/10.1002/ece3.6351

Green Larsen, K., Mitzenmacher, M. & Tsourakakis, C. (2020). Clustering with a faulty oracle. In Y. Huang, I. King, T.-Y. Liu & M. van Steen (Eds.), WWW '20: Proceedings of The Web Conference 2020 (pp. 2831-2834). Association for Computing Machinery. https://doi.org/10.1145/3366423.3380045

Sporbert, M., Keil, P., Seidler, G., Bruelheide, H., Jandt, U., Aćić, S., Biurrun, I., Campos, J. A., Čarni, A., Chytrý, M., Ćušterevska, R., Dengler, J., Golub, V., Jansen, F., Kuzemko, A., Lenoir, J., Marceno, C., Moeslund, J. E., Pérez-Haase, A. ... Welk, E. (2020). Testing macroecological abundance patterns: the relationship between local abundance and range size, range position and climatic suitability among European vascular plants. Journal of Biogeography, 47(10), 2210-2222. https://doi.org/10.1111/jbi.13926

Damgaard, C., Moeslund, J. E. & Wind, P. (2020). Changes in the abundance of Danish orchids over the past 30 years. Diversity, 12(6), Article 244. https://doi.org/10.3390/d12060244

Afshani, P., van Duijn, I., Killmann, R. & Nielsen, J. S. (2020). A lower bound for jumbled indexing. In S. Chawla (Ed.), Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms (pp. 592-606). Association for Computing Machinery. https://doi.org/10.1137/1.9781611975994.36

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

Freksen, C. B. & Larsen, K. G. (2020). On Using Toeplitz and Circulant Matrices for Johnson–Lindenstrauss Transforms. Algorithmica, 82(2), 338-354. https://doi.org/10.1007/s00453-019-00644-y

Brunbjerg, A. K., Bruun, H. H., Dalby, L., Classen, A. T., Fløjgaard, C., Frøslev, T. G., Hansen, O. L. P., Høye, T. T., Moeslund, J. E., Svenning, J.-C. & Ejrnæs, R. (2020). Multi-taxon inventory reveals highly consistent biodiversity responses to ecospace variation. Oikos, 129(9), 1381-1392. https://doi.org/10.1111/oik.07145

Berglin, E. & Brodal, G. S. (2020). A Simple Greedy Algorithm for Dynamic Graph Orientation. Algorithmica, 82(2), 245-259. https://doi.org/10.1007/s00453-018-0528-0

Damgård, I., Larsen, K. G. & Nielsen, J. B. (2019). Communication Lower Bounds for Statistically Secure MPC, With or Without Preprocessing. In A. Boldyreva & D. Micciancio (Eds.), Advances in Cryptology – CRYPTO 2019 - 39th Annual International Cryptology Conference, Proceedings (Vol. II, pp. 61-84). Springer. https://doi.org/10.1007/978-3-030-26951-7_3

Afshani, P., Fagerberg, R., Hammer, D., Jacob, R., Kostitsyna, I., Meyer, U., Penschuck, M. & Sitchinava, N. (2019). Fragile complexity of comparison-based algorithms. In M. A. Bender, O. Svensson & G. Herman (Eds.), 27th Annual European Symposium on Algorithms, ESA 2019 Article 2 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ESA.2019.2

Larsen, K. G. (2019). Constructive Discrepancy Minimization with Hereditary L2 Guarantees. In R. Niedermeier & C. Paul (Eds.), 36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019) Article 48 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.STACS.2019.48

Grønlund, A., Larsen, K. G. & Mathiasen, A. (2019). Optimal Minimal Margin Maximization with Boosting. In K. Chaudhuri & R. Salakhutdinov (Eds.), 36th International Conference on Machine Learning, ICML 2019 (Vol. 97, pp. 7734-7743). International Machine Learning Society (IMLS). http://proceedings.mlr.press/v97/mathiasen19a/mathiasen19a.pdf

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

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

Jiang, S. & Larsen, K. G. (2019). A Faster External Memory Priority Queue with DecreaseKeys. In T. M. Chan (Ed.), Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms (Vol. PRDA19, pp. 1331-1343). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611975482.81

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. (2014). ON range searching in the group model and combinatorial discrepancy. S I A M Journal on Computing, 43(2), 673-686. https://doi.org/10.1137/120865240

Arge, L., Brodal, G. S., Truelsen, J. & Tsirogiannis, C. (2013). An optimal and practical cache-oblivious algorithm for computing multiresolution rasters. In Algorithms – ESA 2013: 21st Annual European Symposium, Sophia Antipolis, France, September 2-4, 2013. Proceedings (pp. 61-72). Springer VS. https://doi.org/10.1007/978-3-642-40450-4_6

Displaying results 151 to 200 out of 453

Revised 01.09.2025

Publications

Head of research