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Martin Lackner

Privatdoz. Dipl.-Ing. Dr.techn.

Martin Lackner

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Contact

2025S

 

2024

  • Repeated fair allocation of indivisible items / Igarashi, A., Lackner, M., Nardi, O., & Novaro, A. (2024). Repeated fair allocation of indivisible items. In AAAI’24/IAAI’24/EAAI’24: Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial Intelligence (pp. 9781–9789). AAAI Press. https://doi.org/10.1609/AAAI.V38I9.28837
    Project: SuDeMa (2019–2025)
  • Phragmén's voting methods and justified representation / Brill, M., Freeman, R., Janson, S., & Lackner, M. (2024). Phragmén’s voting methods and justified representation. Mathematical Programming, 203, 47–76. https://doi.org/10.1007/s10107-023-01926-8
    Download: PDF (607 KB)
    Project: SuDeMa (2019–2025)

2023

2022

  • Liquid Democracy with Ranked Delegations / Brill, M., Delemazure, T., George, A.-M., Lackner, M., & Schmidt-Kraepelin, U. (2022). Liquid Democracy with Ranked Delegations. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (pp. 4884–4891). AAAI Press. https://doi.org/10.1609/aaai.v36i5.20417
    Project: SuDeMa (2019–2025)
  • Participatory Budgeting with Donations and Diversity Constraints / Chen, J., Lackner, M., & Maly, J. (2022). Participatory Budgeting with Donations and Diversity Constraints. In Proceedings of the AAAI Conference on Artificial Intelligence (pp. 9323–9330). AAAI Press. https://doi.org/10.1609/aaai.v36i9.21163
    Project: SuDeMa (2019–2025)
  • How to Sample Approval Elections? / Szufa, S., Faliszewski, P., Janeczko, L., Lackner, M., Slinko, A., Sornat, K., & Talmon, N. (2022). How to Sample Approval Elections? In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22) (pp. 496–502). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2022/71
    Project: SuDeMa (2019–2025)

2021

  • Computing Kemeny Rankings from d-Euclidean Preferences / Hamm, T., Lackner, M., & Rapberger, A. (2021). Computing Kemeny Rankings from d-Euclidean Preferences. In Algorithmic Decision Theory (pp. 147–161). https://doi.org/10.1007/978-3-030-87756-9_10
  • Fairness in Long-Term Participatory Budgeting / Lackner, M., Maly, J., & Rey, S. (2021). Fairness in Long-Term Participatory Budgeting. In AAMAS ’21: 20th International Conference on Autonomous Agents and Multiagent Systems (pp. 1566–1568). http://hdl.handle.net/20.500.12708/58559
    Project: SuDeMa (2019–2025)
  • Fairness in Long-Term Participatory Budgeting / Lackner, M., Maly, J., & Rey, S. (2021). Fairness in Long-Term Participatory Budgeting. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. IJCAI 2021 - 30th International Joint Conference on Artificial Intelligence, Montreal, Canada, Canada. https://doi.org/10.24963/ijcai.2021/42
    Project: SuDeMa (2019–2025)
  • Approval-Based Shortlisting / Lackner, M., & Maly, J. (2021). Approval-Based Shortlisting. In AAMAS ’21: 20th International Conference on Autonomous Agents and Multiagent Systems, Virtual Event, United Kingdom, May 3-7, 2021 (pp. 737–745). http://hdl.handle.net/20.500.12708/58557
  • Consistent approval-based multi-winner rules / Lackner, M., & Skowron, P. (2021). Consistent approval-based multi-winner rules. Journal of Economic Theory, 192(105173), 105173. https://doi.org/10.1016/j.jet.2020.105173

2020

2019

  • A Quantitative Analysis of Multi-Winner Rules / Lackner, M., & Skowron, P. (2019). A Quantitative Analysis of Multi-Winner Rules. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, {IJCAI} 2019, Macao, China, August 10-16, 2019. IJCAI 2019 - 28th International Joint Conference on Artificial Intelligence, Macao, China. ijcai.org. https://doi.org/10.24963/ijcai.2019
    Project: SuDeMa (2019–2025)
  • On Rational Delegations in Liquid Democracy / Bloembergen, D., Grossi, D., & Lackner, M. (2019). On Rational Delegations in Liquid Democracy. In Proceedings of the AAAI Conference on Artificial Intelligence (pp. 1796–1803). AAAI Press. https://doi.org/10.1609/aaai.v33i01.33011796
    Project: SuDeMa (2019–2025)
  • Aggregating Expert Opinions in Support of Medical Diagnostic Decision-Making / Gangl, C., Lackner, M., Maly, J., & Woltran, S. (2019). Aggregating Expert Opinions in Support of Medical Diagnostic Decision-Making. In Knowledge Representation for Health Care/ProHealth, KR4HC 2019 (pp. 56–62). http://hdl.handle.net/20.500.12708/57907
    Projects: START (2014–2022) / SuDeMa (2019–2025)

2018

  • Multiwinner Elections With Diversity Constraints / Lackner, M., Bredereck, R., Faliszewski, P., Igarashi, A., & Skowron, P. (2018). Multiwinner Elections With Diversity Constraints. In Proceedings of the Thirty-Second {AAAI} Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th {AAAI} Symposium on Educational Advances in Artificial Intelligence (EAAI-18) (pp. 933–940). AAAI Press. http://hdl.handle.net/20.500.12708/57541
    Projects: FAIR (2013–2018) / START (2014–2022)
  • Effective Heuristics for Committee Scoring Rules / Lackner, M., Faliszewski, P., Peters, D., & Talmon, N. (2018). Effective Heuristics for Committee Scoring Rules. In Proceedings of the Thirty-Second {AAAI} Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th {AAAI} Symposium on Educational Advances in Artificial Intelligence (EAAI-18) (pp. 1023–1030). AAAI Press. http://hdl.handle.net/20.500.12708/57542
    Projects: FAIR (2013–2018) / START (2014–2022)
  • On the Complexity of Extended and Proportional Justified Representation / Lackner, M., Aziz, H., Elkind, E., Huang, S., Sánchez-Fernández, L., & Skowron, P. (2018). On the Complexity of Extended and Proportional Justified Representation. In Proceedings of the Thirty-Second {AAAI} Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th {AAAI} Symposium on Educational Advances in Artificial Intelligence (EAAI-18) (pp. 902–909). AAAI Press. http://hdl.handle.net/20.500.12708/57543
    Projects: FAIR (2013–2018) / START (2014–2022)
  • Consistent Approval-Based Multi-Winner Rules / Lackner, M., & Skowron, P. (2018). Consistent Approval-Based Multi-Winner Rules. In Proceedings of the 2018 ACM Conference on Economics and Computation. ACM Conference on Economics and Computation, Ithaca, United States of America (the). https://doi.org/10.1145/3219166.3219170
    Projects: FAIR (2013–2018) / START (2014–2022)
  • Computing the Schulze Method for Large-Scale Preference Data Sets / Csar, T., Lackner, M., & Pichler, R. (2018). Computing the Schulze Method for Large-Scale Preference Data Sets. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. IJCAI - International Joint Conference on Artificial Intelligence, Stockholm, Sweden. ijcai.org. https://doi.org/10.24963/ijcai.2018/25
    Projects: FAIR (2013–2018) / HyperTrac (2018–2022) / START (2014–2022)
  • Approval-Based Multi-Winner Rules and Strategic Voting / Lackner, M., & Skowron, P. (2018). Approval-Based Multi-Winner Rules and Strategic Voting. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. IJCAI - International Joint Conference on Artificial Intelligence, Stockholm, Sweden. ijcai.org. https://doi.org/10.24963/ijcai.2018/47
    Projects: FAIR (2013–2018) / START (2014–2022)
  • A Quantitative Analysis of Multi-Winner Rules / Lackner, M., & Skowron, P. (2018). A Quantitative Analysis of Multi-Winner Rules. In Proceedings of the 7th International Workshop on Computational Social Choice (COMSOC 2018) (pp. 1–29). Computing Research Repository (CoRR). http://hdl.handle.net/20.500.12708/57490
    Projects: FAIR (2013–2018) / START (2014–2022)

2017

  • Winner Determination in Huge Elections with MapReduce. AAAI 2017: 451-458 / Csar, T., Lackner, M., Pichler, R., & Sallinger, E. (2017). Winner Determination in Huge Elections with MapReduce. AAAI 2017: 451-458. In AAAI 2017 (pp. 451–458). http://hdl.handle.net/20.500.12708/57076
    Projects: FAIR (2013–2018) / HINT (2012–2017) / START (2014–2022)
  • Computational Social Choice in the Clouds / Csar, T., Lackner, M., Pichler, R., & Sallinger, E. (2017). Computational Social Choice in the Clouds. In Workshop Präferenzen und Personalisierung in der Informatik bei der Konferenz “Datenbanksysteme für Business, Technologie und Web” (BTW) (pp. 163–167). http://hdl.handle.net/20.500.12708/57077
    Projects: FAIR (2013–2018) / HINT (2012–2017) / START (2014–2022)

2016

  • Winner Determination in Huge Elections with MapReduce / Csar, T., Lackner, M., Pichler, R., & Sallinger, E. (2016). Winner Determination in Huge Elections with MapReduce. In M. Endres, N. Mattei, & A. Pfandler (Eds.), 10th Multidisciplinary Workshop on Advances in Preference Handling (p. 7). http://hdl.handle.net/20.500.12708/56661
    Projects: FAIR (2013–2018) / HINT (2012–2017) / SEE (2012–2016) / START (2014–2022)

2015

  • Structure in Dichotomous Preferences / Elkind, E., & Lackner, M. (2015). Structure in Dichotomous Preferences. In Q. Yang & M. Wooldridge (Eds.), Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, July 25-31, 2015 (pp. 2019–2025). AAAI Press. http://hdl.handle.net/20.500.12708/56255
    Project: START (2014–2022)
  • The Complexity of Recognizing Incomplete Single-Crossing Preferences / Elkind, E., Faliszewski, P., Lackner, M., & Obraztsova, S. (2015). The Complexity of Recognizing Incomplete Single-Crossing Preferences. In B. Bonet & S. Koenig (Eds.), Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 25-30, 2015, Austin, Texas, USA (pp. 865–871). AAAI Press. http://hdl.handle.net/20.500.12708/56103
    Project: SEE (2012–2016)
  • Manipulation of k-Approval in Nearly Single-Peaked Electorates / Erdélyi, G., Lackner, M., & Pfandler, A. (2015). Manipulation of k-Approval in Nearly Single-Peaked Electorates. In T. Walsh (Ed.), Algorithmic Decision Theory (pp. 71–85). Springer. https://doi.org/10.1007/978-3-319-23114-3_5
    Projects: FAIR (2013–2018) / START (2014–2022)

2014

  • Detecting structure in permutations and preferences / Lackner, M. (2014). Detecting structure in permutations and preferences [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2014.24943
    Download: PDF (1.08 MB)
  • A Parameterized Complexity Analysis of Generalized CP-Nets / Kronegger, M., Lackner, M., Pfandler, A., & Pichler, R. (2014). A Parameterized Complexity Analysis of Generalized CP-Nets. In M. R. Fellows, S. Gaspers, & T. Walsh (Eds.), Proceedings of the 2nd Workshop on the Parameterized Complexity of Computational Reasoning (PCCR) (p. 2). http://hdl.handle.net/20.500.12708/55773
    Project: FAIR (2013–2018)
  • The Likelihood of Structure in Preference Profiles / Bruner, M.-L., & Lackner, M. (2014). The Likelihood of Structure in Preference Profiles. 8th Multidisciplinary Workshop on Advances in Preference Handling, Quebec, Kanada, Non-EU. http://hdl.handle.net/20.500.12708/85942
  • On Detecting Nearly Structured Preference Profiles / Lackner, M., & Elkind, E. (2014). On Detecting Nearly Structured Preference Profiles. Workshop on Challenges in Algorithmic Social Choice (CASC), Bad Belzig, Deutschland, EU. http://hdl.handle.net/20.500.12708/85941
  • On the Parameterized Complexity of Generalized CP-Nets / Kronegger, M., Lackner, M., Pfandler, A., & Pichler, R. (2014). On the Parameterized Complexity of Generalized CP-Nets. Workshop on Challenges in Algorithmic Social Choice (CASC), Bad Belzig, Deutschland, EU. http://hdl.handle.net/20.500.12708/85939
    Project: FAIR (2013–2018)
  • On Detecting Nearly Structured Preference Profiles / Elkind, E., & Lackner, M. (2014). On Detecting Nearly Structured Preference Profiles. In C. E. Brodley & P. Stone (Eds.), Proceedings of the Twenty-Eighth AAAI Conference on Aritifical Intelligence (pp. 661–667). http://hdl.handle.net/20.500.12708/55796
  • A Parameterized Complexity Analysis of Generalized CP-Nets / Kronegger, M., Lackner, M., Pfandler, A., & Pichler, R. (2014). A Parameterized Complexity Analysis of Generalized CP-Nets. In C. E. Brodley & P. Stone (Eds.), Proceedings of the Twenty-Eighth AAAI Conference on Aritifical Intelligence (pp. 1091–1097). http://hdl.handle.net/20.500.12708/55793
    Project: FAIR (2013–2018)
  • Incomplete Preferences in Single-Peaked Electorates / Lackner, M. (2014). Incomplete Preferences in Single-Peaked Electorates. In C. E. Brodley & P. Stone (Eds.), Proceedings of the Twenty-Eighth AAAI Conference on Aritifical Intelligence (pp. 742–748). http://hdl.handle.net/20.500.12708/55786

2013

2012

  • Fixed-Parameter Algorithms for Finding Minimal Models / Lackner, M., & Pfandler, A. (2012). Fixed-Parameter Algorithms for Finding Minimal Models. Logic and interactions 2012, CIRM, Marseille, France, EU. http://hdl.handle.net/20.500.12708/85367
  • Permutation Pattern Matching and its Parameterized Complexity / Lackner, M., & Bruner, M.-L. (2012). Permutation Pattern Matching and its Parameterized Complexity. Conference on Computability in Europe CiE, Cambridge, Great Britain, EU. http://hdl.handle.net/20.500.12708/85363
  • A Fast Algorithm for Permutation Pattern Matching / Lackner, M. (2012). A Fast Algorithm for Permutation Pattern Matching. Universität Siegen, Siegen, Deutschland, EU. http://hdl.handle.net/20.500.12708/85375
  • Fixed-Parameter Algorithms for Finding Minimal Models / Lackner, M., & Pfandler, A. (2012). Fixed-Parameter Algorithms for Finding Minimal Models. Universität Siegen, Siegen, Deutschland, EU. http://hdl.handle.net/20.500.12708/85373
  • Fixed-Parameter Algorithms for Closed World Reasoning / Lackner, M., & Pfandler, A. (2012). Fixed-Parameter Algorithms for Closed World Reasoning. In L. D. Raedt, C. Bessiere, D. Dubois, P. Doherty, P. Frasconi, F. Heintz, & P. Lucas (Eds.), Proceedings of the ECAI Conference (pp. 492–497). IOS Press. http://hdl.handle.net/20.500.12708/54183
  • Multicut on Graphs of Bounded Clique-Width / Lackner, M., Pichler, R., Rümmele, S., & Woltran, S. (2012). Multicut on Graphs of Bounded Clique-Width. In G. Lin (Ed.), Combinatorial Optimization and Applications (pp. 115–126). Springer. https://doi.org/10.1007/978-3-642-31770-5_11
    Project: TTPC (2008–2012)
  • A Fast Algorithm for Permutation Pattern Matching Based on Alternating Runs / Lackner, M., & Bruner, M.-L. (2012). A Fast Algorithm for Permutation Pattern Matching Based on Alternating Runs. In F. Fomin & P. Kaski (Eds.), Algorithm Theory – SWAT 2012 (pp. 261–270). Springer. https://doi.org/10.1007/978-3-642-31155-0_23
  • Fixed-Parameter Algorithms for Finding Minimal Models / Lackner, M., & Pfandler, A. (2012). Fixed-Parameter Algorithms for Finding Minimal Models. In G. Brewka, T. Eiter, & S. McIlraith (Eds.), Proceedings of 13#^{th} int. conf. on Principles of Knowledge Representation and Reasoning (p. 11). AAAI Press. http://hdl.handle.net/20.500.12708/54179
    Project: TTPC (2008–2012)
  • The Complexity of Nearly Single-Peaked Consistency / Erdély, G., Lackner, M., & Pfandler, A. (2012). The Complexity of Nearly Single-Peaked Consistency. In F. Brandt & P. Faliszewski (Eds.), Proceedings of fourth int. conference on Computational Social Choice (p. 12). http://hdl.handle.net/20.500.12708/54178
    Project: TTPC (2008–2012)

2011

  • On the fixed-parameter tractability of computing minimal models / Lackner, M. (2011). On the fixed-parameter tractability of computing minimal models. Workshop - Parameterized Complexity: Not About Graphs, Darwin, Australien, Non-EU. http://hdl.handle.net/20.500.12708/85368
  • Hardness results for Weighted Minimal Model SAT / Pfandler, A., & Lackner, M. (2011). Hardness results for Weighted Minimal Model SAT. Workshop - Parameterized Complexity: Not About Graphs, Darwin, Australien, Non-EU. http://hdl.handle.net/20.500.12708/85217
  • Algorithms for finding minimal models / Lackner, M., & Pfandler, A. (2011). Algorithms for finding minimal models. Workshop - Parameterized Complexity: Not About Graphs, Darwin, Australien, Non-EU. http://hdl.handle.net/20.500.12708/85216

2010