Publications

Brodal, G. S. & Wild, S. (2023). Funnelselect: Cache-Oblivious Multiple Selection. In I. Li Gortz, M. Farach-Colton, S. J. Puglisi & G. Herman (Eds.), 31st Annual European Symposium on Algorithms, ESA 2023 (pp. 25:1-25:17). Article 25 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ESA.2023.25

Brodal, G. S., Rysgaard, C. M., Schou, J. K. R. & Svenning, R. (2023). Space-Efficient Functional Offline-Partially-Persistent Trees with Applications to Planar Point Location. In P. Morin & S. Suri (Eds.), Algorithms and Data Structures: 18th International Symposium, WADS 2023, Montreal, QC, Canada, July 31 – August 2, 2023, Proceedings (pp. 644-659). Springer. https://doi.org/10.1007/978-3-031-38906-1_43

Brodal, G. S. & Wild, S. (2024). Deterministic Cache-Oblivious Funnelselect. In H. L. Bodlaender (Ed.), 19th Scandinavian Symposium on Algorithm Theory, SWAT 2024 Article 17 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.SWAT.2024.17

Brodal, G. S. (2024). Bottom-Up Rebalancing Binary Search Trees by Flipping a Coin. In A. Z. Broder & T. Tamir (Eds.), 12th International Conference on Fun with Algorithms, FUN 2024 Article 6 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.FUN.2024.6

Brodal, G. S., Fagerberg, R. & Rysgaard, C. M. (2024). On Finding Longest Palindromic Subsequences Using Longest Common Subsequences. In T. Chan, J. Fischer, J. Iacono & G. Herman (Eds.), 32nd Annual European Symposium on Algorithms, ESA 2024 Article 35 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ESA.2024.35

Brodal, G. S. & Rysgaard, C. M. (2025). Pure Binary Finger Search Trees. In I.-O. Bercea & R. Pagh (Eds.), 8th SIAM Symposium on Simplicity of Algorithms, SOSA 2025 (pp. 172-195). Society for Industrial and Applied Mathematics.

Brodal, G. S., Lagogiannis, G. & Tarjan, R. E. (2025). Strict Fibonacci Heaps. ACM Transactions on Algorithms, 21(2), Article 15. https://doi.org/10.1145/3707692

Brodal, G. S. (1997). Worst Case Efficient Data Structures. Department of Computer Science, Aarhus University.

Brodal, G. S. (2025). A Simple Integer Successor-Delete Data Structure. In P. Mutzel & N. Prezza (Eds.), 23rd International Symposium on Experimental Algorithms, SEA 2025 Article 8 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.SEA.2025.8

Brodal, G. S. (2025). Bottom-up rebalancing binary search trees by flipping a coin. Theoretical Computer Science, 1055, Article 115543. https://doi.org/10.1016/j.tcs.2025.115543

Brodal, G. S., Rysgaard, C. M. & Svenning, R. (2025). Buffered Partially-Persistent External-Memory Search Trees. In A. Benoit, H. Kaplan, S. Wild, S. Wild & G. Herman (Eds.), 33rd Annual European Symposium on Algorithms, ESA 2025 Article 82 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ESA.2025.82

Brodal, G. S., Iacono, J., Meyer, U., Sitchinava, N., Goodrich, M. T., Lo, J., Pagan, V. & Svenning, R. (2025). External-Memory Priority Queues with Optimal Insertions. In A. Benoit, H. Kaplan, S. Wild, S. Wild & G. Herman (Eds.), 33rd Annual European Symposium on Algorithms, ESA 2025 Article 5 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ESA.2025.5

Brody, J. E. & Larsen, K. G. (2015). Adapt or Die: Polynomial Lower Bounds for Non-Adaptive Dynamic Data Structures. Theory of Computing, 11(19), 471-489. https://doi.org/10.4086/toc.2015.v011a019

Bruelheide, H., Dengler, J., Jiménez-Alfaro, B., Purschke, O., Hennekens, S. M., Chytrý, M., Pillar, V. D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R. K., Peyre, G., Sabatini, F. M. ... Zverev, A. (2019). sPlot – A new tool for global vegetation analyses. Journal of Vegetation Science, 30(2), 161-186. https://doi.org/10.1111/jvs.12710

Brunbjerg, A. K., Bruun, H. H., Moeslund, J. E., Sadler, J. P., Svenning, J.-C. & Ejrnæs, R. (2015). Ecospace - a unified framework for understanding variation in biodiversity. Poster session presented at Biodiversitetssymposiet 2015, Aarhus , Denmark.

Brunbjerg, A. K., Bladt, J., Moeslund, J. E. & Ejrnæs, R. (2015). Naturen på kort - nye værktøjer målretter indsatsen for truede arter. Aktuel Naturvidenskab, (3), 12-15.

Brunbjerg, A. K., Bladt, J., Brink, M., Fredshavn, J. R., Mikkelsen, P., Moeslund, J. E., Nygaard, B., Skov, F. & Ejrnæs, R. (2016). Development and implementation of a High Nature Value (HNV) farming indicator for Denmark. Ecological Indicators, 61(2), 274-281. https://doi.org/10.1016/j.ecolind.2015.09.027

Brunbjerg, A. K., Bruun, H. H., Moeslund, J. E., Sadler, J. P., Svenning, J.-C. & Ejrnæs, R. (2017). Ecospace: a unified framework for understanding variation in terrestrial biodiversity. Basic and Applied Ecology, 18, 86-94. https://doi.org/10.1016/j.baae.2016.09.002

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

Brunbjerg, A. K., Fløjgaard, C., Frøslev, T. G., Andersen, D. K., Bruun, H. H., Dalby, L., Goldberg, I., Juhl Lehmann, L., Moeslund, J. E. & Ejrnæs, R. (2022). Scrub encroachment promotes biodiversity in temperate European wetlands under eutrophic conditions. Ecology and Evolution, 12(11), Article e9445. https://doi.org/10.1002/ece3.9445

Brunbjerg, A. K., Bladt, J., Ejrnæs, R., Nygaard, B. & Moeslund, J. E. (2026). Designing a long-term monitoring program for Denmark's national parks. Poster session presented at BioMonWeek, Montpellier, France.

Bucarelli, M. S., Larsen, M. F., Schwiegelshohn, C. & Toftrup, M. B. (2023). On Generalization Bounds for Projective Clustering.

Bucarelli, M. S., Larsen, M. F., Schwiegelshohn, C. & Toftrup, M. B. (2023). On Generalization Bounds for Projective Clustering. In Advances in Neural Information Processing Systems https://papers.nips.cc/paper_files/paper/2023/hash/e30bf4765ae6b16a87fb4d7b0b3b3dec-Abstract-Conference.html

Bulboaca, N., Jamalabadi, S. & Schwiegelshohn, C. (2026). k-Center with outliers in sliding windows. Operations Research Letters, 69, Article 107504. https://doi.org/10.1016/j.orl.2026.107504

Burkhardt, J., Caragiannis, I., Fehrs, K., Russo, M., Schwiegelshohn, C. & Shyam, S. (2024). Low-Distortion Clustering with Ordinal and Limited Cardinal Information. Proceedings of the AAAI Conference on Artificial Intelligence, 38(9), 9555-9563. https://doi.org/10.1609/aaai.v38i9.28811

Burkhardt, J., Keller, H. J., Orlandi, C. & Schwiegelshohn, C. (2025). Distributed Differentially Private Data Analytics via Secure Sketching. In Forty-second International Conference on Machine Learning: ICML 2025 (Vol. 267, pp. 5913-5942). Article 10733 https://openreview.net/forum?id=2Snksn3U47

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

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

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

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

Caragiannis, I., Larsen, K. G. & Shyam, S. (2026). A New Lower Bound for Multicolor Discrepancy with Applications to Fair Division. In R. Lavi & J. Zhang (Eds.), Algorithmic Game Theory: 18th International Symposium, SAGT 2025, Bath, UK, September 2–5, 2025, Proceedings (pp. 228-246). Springer. https://doi.org/10.1007/978-3-032-03639-1_13

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

Cazzaniga, S. G., Lauber, T., van den Hoogen, J., Beaury, E. M., Bueno, C. G., Bever, J. D., Damasceno, G., Catford, J., Lenoir, J., Martin, A., Mori, A. S., Novakovskiy, A., Gutiérrez, A. G., González-Robles, A., de Gasper, A. L., Moles, A., Stanisci, A., Csecserits, A., Jentsch, A. ... Delavaux, C. S. (2026). Mycorrhizal strategy of non-native plants varies with biome and disturbance. Nature Ecology and Evolution, 10(9), 1644-1657. https://doi.org/10.1038/s41559-026-03144-9

Chakraborty, D., Kamma, L. & Larsen, K. G. (2018). Tight cell probe bounds for succinct boolean matrix-Vector multiplication. In STOC 2018 - Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing (pp. 1297-1306). Association for Computing Machinery. https://doi.org/10.1145/3188745.3188830

Chan, T. M., Larsen, K. G. & Patrascu, M. (2011). Orthogonal Range Searching on the RAM, Revisited. In Proceedings of the 27th annual ACM symposium on Computational geometry (pp. 1-10). Association for Computing Machinery. https://doi.org/10.1145/1998196.1998198

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

Chan, T. M. & Wilkinson, B. T. (2011). Bichromatic Line Segment Intersection Counting in O(n sqrt{log n}) Time. Paper presented at Canadian Conference on Computational Geometry, Canada. http://www.cccg.ca/proceedings/2011/papers/paper83.pdf

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

Chan, T. M. & Wilkinson, B. T. (2013). Adaptive and Approximate Orthogonal Range Counting. In S. Khanna (Ed.), Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2013 (pp. 241-251). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611973105.18

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. & Wilkinson, B. T. (2016). Adaptive and approximate orthogonal range counting. ACM Transactions on Algorithms, 12(4), 45:1-45:15. Article 45. https://doi.org/10.1145/2830567

Cheng, P. & Afshani, P. (2023). An Optimal Lower Bound for Simplex Range Reporting. In T. Kavitha & K. Mehlhorn (Eds.), 6th Symposium on Simplicity in Algorithms (SOSA 2023) (pp. 272-277). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611977585.ch25

Chung, E. & Larsen, K. G. (2023). Stronger 3SUM-Indexing Lower Bounds. In N. Bansal & V. Nagarajan (Eds.), Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA) (pp. 444-455). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611977554.ch19

Chytrý, M., Hennekens, S. M., Jiménez-Alfaro, B., Knollová, I., Dengler, J., Jansen, F., Landucci, F., Schaminée, J. H. J., Aćić, S., Agrillo, E., Ambarlı, D., Angelini, P., Apostolova, I., Attorre, F., Berg, C., Bergmeier, E., Biurrun, I., Botta-Dukát, Z., Brisse, H. ... Yamalov, S. (2015). European Vegetation Archive (EVA): an integrated database of European vegetation plots. Applied Vegetation Science, 19(1), 173-180. https://doi.org/10.1111/avsc.12191

Clifford, R., Jørgensen, A. G. & Larsen, K. G. (2015). New Unconditional Hardness Results for Dynamic and Online Problems. In 56th IEEE Symposium on Foundations of Computer Science (FOCS) Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS IEEE Computer Society Press. http://arxiv.org/pdf/1504.01836v1.pdf

Clifford, R., Grønlund, A., Larsen, K. G. & Starikovskaya, T. (2018). Upper and lower bounds for dynamic data structures on strings. In R. Niedermeier & B. Vallée (Eds.), 35th Symposium on Theoretical Aspects of Computer Science, STACS 2018 (Vol. 96, pp. 22:1-22:14). Article 22 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.STACS.2018.22

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

Cohen-Addad, V., Saulpic, D. & Schwiegelshohn, C. (2021). A new coreset framework for clustering. In S. Khuller & V. V. Williams (Eds.), STOC 2021 - Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing (pp. 169-182). Association for Computing Machinery. https://doi.org/10.1145/3406325.3451022

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Publications

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