Publications

Aden-Ali, I., Høgsgaard, M. M., Larsen, K. G. & Zhivotovskiy, N. (2024). Majority-of-Three: The Simplest Optimal Learner? In Proceedings of Thirty Seventh Conference on Learning Theory (Vol. 247, pp. 22-45). PMLR. https://proceedings.mlr.press/v247/aden-ali24a.html

Afshani, P., Killmann, R. & Larsen, K. G. (2024). Hierarchical categories in colored searching. Computational Geometry, 121, Article 102090. https://doi.org/10.1016/j.comgeo.2024.102090

Afshani, P. & Cheng, P. (2024). On Semialgebraic Range Reporting. Discrete & Computational Geometry, 71(1), 4-39. https://doi.org/10.1007/s00454-023-00574-1

Afshani, P. & Schwiegelshohn, C. (2024). Optimal Coresets for Low-Dimensional Geometric Median. In International Conference on Machine Learning (pp. 262-270). PMLR.

Alon, N., Bousquet, O., Larsen, K. G., Moran, S. & Moran, S. (2024). Diagonalization Games. The American Mathematical Monthly, 131(10), 866-879. https://doi.org/10.1080/00029890.2024.2393992

Alon, N., Grønlund, A., Jørgensen, S. F. & Larsen, K. G. (2024). Sublinear Time Shortest Path in Expander Graphs. In R. Kralovic & A. Kucera (Eds.), 49th International Symposium on Mathematical Foundations of Computer Science, MFCS 2024 (pp. 8:1-8:13). Article 8 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.MFCS.2024.8

Brewer, B., Brodal, G. S. & Wang, H. (2024). Dynamic Convex Hulls for Simple Paths. In W. Mulzer & J. M. Phillips (Eds.), 40th International Symposium on Computational Geometry, SoCG 2024 Article 24 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.SoCG.2024.24

Bringmann, K., Grønlund, A., Künnemann, M. & Larsen, K. G. (2024). The NFA Acceptance Hypothesis: Non-Combinatorial and Dynamic Lower Bounds. In V. Guruswami (Ed.), 15th Innovations in Theoretical Computer Science Conference (ITCS 2024) (pp. 22:1-22:25). Article 22 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ITCS.2024.22

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. & 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., 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

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

da Cunha, A., Høgsgaard, M. M. & Larsen, K. G. (2024). Optimal Parallelization of Boosting. Abstract from NeurIPS'24: 38th Conference on Neural Information Processing Systems, Vancouver, Canada.

Daniel Kissling, W., Shi, Y., Wang, J., Walicka, A., George, C., Moeslund, J. E. & Gerard, F. (2024). Towards consistently measuring and monitoring habitat condition with airborne laser scanning and unmanned aerial vehicles. Ecological Indicators, 169, Article 112970. https://doi.org/10.1016/j.ecolind.2024.112970

Draganov, A. A., Saulpic, D. & Schwiegelshohn, C. (2024). Settling Time vs. Accuracy Tradeoffs for Clustering Big Data. Proceedings of the ACM on Management of Data, 2(3), Article 173. https://doi.org/10.1145/3654976

Ejrnæs, R., Dalby, L., Bladt, J., Søndergaard, S. A., Dümke, L., Fløjgaard, C., Bruun, L. D., Ejrnæs, D. D., Moeslund, J. E. & Bruun, H. H. (2024). Opportunities and barriers for promoting biodiversity in Danish beef production. iScience, 27(12), Article 111422. https://doi.org/10.1016/j.isci.2024.111422

Fleischhacker, N., Larsen, K. G., Obremski, M. & Simkin, M. (2024). Invertible Bloom Lookup Tables with Less Memory and Randomness. In T. Chan, J. Fischer, J. Iacono & G. Herman (Eds.), 32nd Annual European Symposium on Algorithms, ESA 2024 Article 54 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ESA.2024.54

Hanneke, S., Larsen, K. G. & Zhivotovskiy, N. (2024). Revisiting Agnostic PAC Learning. In Proceedings - 2024 IEEE 65th Annual Symposium on Foundations of Computer Science, FOCS 2024 (pp. 1968-1982). IEEE. https://doi.org/10.1109/FOCS61266.2024.00118

Høgsgaard, M. M., Kamma, L., Larsen, K. G., Nelson, J. & Schwiegelshohn, C. (2024). Sparse Dimensionality Reduction Revisited. In International Conference on Machine Learning (pp. 18454-18469). PMLR.

Høgsgaard, M. M., Larsen, K. G. & Mathiasen, M. E. (2024). The Many Faces of Optimal Weak-to-Strong Learning. https://arxiv.org/pdf/2408.17148

Kalavasis, A., Karbasi, A., Larsen, K. G., Velegkas, G. & Zhou, F. (2024). Replicable Learning of Large-Margin Halfspaces. In Proceedings of the 41 st International Conference on Machine Learning (Vol. 235, pp. 22861-22878). MLResearch Press.

Karbasi, A. & Larsen, K. G. (2024). The Impossibility of Parallelizing Boosting. In Proceedings of Machine Learning Research (Vol. 237, pp. 635-653)

Knollová, I., Chytrý, M., Bruelheide, H., Dullinger, S., Jandt, U., Bernhardt-Römermann, M., Biurrun, I., de Bello, F., Glaser, M., Hennekens, S., Jansen, F., Jiménez-Alfaro, B., Kadaš, D., Kaplan, E., Klinkovská, K., Lenzner, B., Pauli, H., Sperandii, M. G., Verheyen, K. ... Essl, F. (2024). ReSurveyEurope: A database of resurveyed vegetation plots in Europe. Journal of Vegetation Science, 35(2), Article e13235. https://doi.org/10.1111/jvs.13235

Larsen, K. G. (2024). Bagging is an Optimal PAC Learner (Extended Abstract). In K. Larson (Ed.), Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24) (pp. 8411-8415). IJCAI Organization. https://doi.org/10.24963/ijcai.2024/932

Larsen, K. G. (2024). From TCS to Learning Theory. In R. Kralovic & A. Kucera (Eds.), 49th International Symposium on Mathematical Foundations of Computer Science, MFCS 2024 Article 4 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.MFCS.2024.4

Larsen, K. G., Pagh, R., Persiano, G., Pitassi, T., Yeo, K. & Zamir, O. (2024). Optimal Non-Adaptive Cell Probe Dictionaries and Hashing. In K. Bringmann, M. Grohe, G. Puppis & O. Svensson (Eds.), 51st International Colloquium on Automata, Languages, and Programming, ICALP 2024 Article 104 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ICALP.2024.104

Leblanc, C., Bonnet, P., Servajean, M., Chytrý, M., Aćić, S., Argagnon, O., Bergamini, A., Biurrun, I., Bonari, G., Campos, J. A., Čarni, A., Ćušterevska, R., De Sanctis, M., Dengler, J., Garbolino, E., Golub, V., Jandt, U., Jansen, F., Lebedeva, M. ... Joly, A. (2024). A deep-learning framework for enhancing habitat identification based on species composition. Applied Vegetation Science, 27(3), Article e12802. https://doi.org/10.1111/avsc.12802

Moeslund, J. E. & Damgaard, C. F. (2024). Predicting Abiotic Soil Characteristics Using Sentinel-2 at Nature-Management-Relevant Spatial Scales and Extents. Remote Sensing, 16(16), Article 3094. https://doi.org/10.3390/rs16163094

Schou, J. K. R. & Wang, B. (2024). PersiSort: A New Perspective on Adaptive Sorting Based on Persistence. In R. I. Nishat (Ed.), Canadian Conference on Computational Geometry: Proceedings of the 36th Canadian Conference on Computational Geometry (CCCG 2024) Brock University, St. Catharines, Canada, July 17 - 19, 2024 (pp. 287-312)

Toftrup, M. B., Loeschcke, S., Belongie, S., J. Kastoryano, M. & Snæbjanarson, V. (2024). LoQT: Low-Rank Adapters for Quantized Pretraining. https://arxiv.org/abs/2405.16528

Zhivotovskiy, N., Larsen, K. G. & Montasser, O. (2024). Derandomizing Multi-Distribution Learning. Abstract from NeurIPS'24: 38th Conference on Neural Information Processing Systems, Vancouver, Canada.

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 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.SoCG.2023.3

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., Cheng, P., Basu Roy, A. & Wei, Z. (2023). On Range Summary Queries. In K. Etessami, U. Feige & G. Puppis (Eds.), 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023) (pp. 7:1-7:17). Article 7 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.ICALP.2023.7

Afshani, P. & Killmann, R. (2023). Rectangle stabbing and orthogonal range reporting lower bounds in moderate dimensions. Computational Geometry: Theory and Applications, 111, Article 101959. https://doi.org/10.1016/j.comgeo.2022.101959

Andersen, A. H., Clausen, K. K., Normand, S., Vikstrøm, T. & Moeslund, J. E. (2023). The influence of landscape characteristics on breeding bird dark diversity. Oecologia, 201(4), 1039-1052. https://doi.org/10.1007/s00442-023-05351-8

Brodal, G. S., Rysgaard, C. M. & Svenning, R. (2023). External Memory Fully Persistent Search Trees. In B. Saha & R. A. Servedio (Eds.), STOC 2023 - Proceedings of the 55th Annual ACM Symposium on Theory of Computing (pp. 1410-1423). Association for Computing Machinery. https://doi.org/10.1145/3564246.3585140

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

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

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

Cohen-Addad, V., Saulpic, D. & Schwiegelshohn, C. (2023). Deterministic Clustering in High Dimensional Spaces: Sketches and Approximation. In 2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS) (pp. 1105-1130). IEEE. https://doi.org/10.1109/FOCS57990.2023.00066

Ejrnæs, R., Moeslund, J. E., Fløjgaard, C., Bladt, J. & Brunbjerg, A. K., (2023). Fagligt grundlag for overvågning af naturnationalparker, Fagligt notat fra DCE – Nationalt Center for Miljø og Energi (2020-...) Vol. 67 https://dce.au.dk/fileadmin/dce.au.dk/Udgivelser/Notater_2023/N2023_67.pdf

Fandina, O. N., Høgsgaard, M. M. & Larsen, K. G. (2023). Barriers for Faster Dimensionality Reduction. In P. Berenbrink, P. Bouyer, A. Dawar & M. M. Kante (Eds.), 40th International Symposium on Theoretical Aspects of Computer Science, STACS 2023 Article 31 Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.STACS.2023.31

Fandina, O. N., Høgsgaard, M. M. & Larsen, K. G. (2023). The Fast Johnson-Lindenstrauss Transform Is Even Faster. In A. Krause, E. Brunskill, K. Cho, B. Engelhardt, S. Sabato & J. Scarlett (Eds.), Proceedings of ICML 2023 (Vol. 202, pp. 9689-9715). MLResearch Press.

Fleischhacker, N., Larsen, K. G. & Simkin, M. (2023). How to Compress Encrypted Data. In C. Hazay & M. Stam (Eds.), Advances in Cryptology – EUROCRYPT 2023: 42nd Annual International Conference on the Theory and Applications of Cryptographic Techniques, Lyon, France, April 23-27, 2023, Proceedings, Part I (pp. 551-577). Springer. https://doi.org/10.1007/978-3-031-30545-0_19

Høgsgaard, M. M., Larsen, K. G. & Ritzert, M. (2023). AdaBoost is not an Optimal Weak to Strong Learner. In A. Krause, E. Brunskill, K. Cho, B. Engelhardt, S. Sabato & J. Scarlett (Eds.), Proceedings of ICML 2023 (Vol. 202, pp. 13118-13140). MLResearch Press.

Kambach, S., Sabatini, F. M., Attorre, F., Biurrun, I., Boenisch, G., Bonari, G., Čarni, A., Carranza, M. L., Chiarucci, A., Chytrý, M., Dengler, J., Garbolino, E., Golub, V., Güler, B., Jandt, U., Jansen, J., Jašková, A., Jiménez-Alfaro, B., Karger, D. N. ... Bruelheide, H. (2023). Climate-trait relationships exhibit strong habitat specificity in plant communities across Europe. Nature Communications, 14(1), Article 712. https://doi.org/10.1038/s41467-023-36240-6

Displaying results 51 to 100 out of 460

Revised 01.09.2025

Publications

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