2017
Hutter, F., Lindauer, M., Balint, A., Bayless, S., Hoos, H., & Leyton-Brown, K. (2017). The Configurable SAT Solver Challenge (CSSC). Artificial intelligence, 243, 1-25.
Kiesel, J., Wachsmuth, H., Al-Khatib, K., & Stein, B. (2017). WAT-SL: A Customizable Web Annotation Tool for Segment Labeling. in A. Penas, & A. Martins (Hrsg.), Proceedings of the EACL 2017 Software Demonstrations (S. 13-16). Association for Computational Linguistics (ACL).
Lindauer, M., Hutter, F., Hoos, H. H., & Schaub, T. (2017). AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract). in C. Sierra (Hrsg.), International Joint Conference on Artificial Intelligence (IJCAI 2017) (S. 5025-5029). AAAI Press/International Joint Conferences on Artificial Intelligence.
Lindauer, M. T., van Rijn, J. N., & Kotthoff, L. (2017). Open Algorithm Selection Challenge 2017 Setup and Scenarios.
Wachsmuth, H., Naderi, N., Habernal, I., Hou, Y., Hirst, G., Gurevych, I., & Stein, B. (2017). Argumentation Quality Assessment: Theory vs. Practice. in Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers) (S. 250-255). Association for Computational Linguistics (ACL).
Wachsmuth, H., & Stein, B. (2017). A Universal Model for Discourse-Level Argumentation Analysis. ACM Transactions on Internet Technology, 17(3), [28].
Wachsmuth, H., Potthast, M., Al-Khatib, K., Ajjour, Y., Puschmann, J., Qu, J., Dorsch, J., Morari, V., Bevendorff, J., & Stein, B. (2017). Building an Argument Search Engine for the Web. in I. Habernal, I. Gurevych, K. Ashley, C. Cardie, N. Green, D. Litman, G. Petasis, C. Reed, N. Slonim, & V. Walker (Hrsg.), Proceedings of the 4th Workshop on Argument Mining (S. 49-59). Association for Computational Linguistics (ACL).
Wachsmuth, H., Naderi, N., Hou, Y., Bilu, Y., Prabhakaran, V., Thijm, T. A., Hirst, G., & Stein, B. (2017). Computational Argumentation Quality Assessment in Natural Language. in Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers (S. 176-187). Association for Computational Linguistics (ACL).
Wachsmuth, H., Stein, B., & Ajjour, Y. (2017). “PageRank” for Argument Relevance. in P. Blunsom, A. Koller, & M. Lapata (Hrsg.), Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, Long Papers (S. 1117-1127). Association for Computational Linguistics (ACL).
Wachsmuth, H., da San Martino, G., Kiesel, D., & Stein, B. (2017). The Impact of Modeling Overall Argumentation with Tree Kernels. in Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (S. 2379-2389). Association for Computational Linguistics (ACL).
Wagner, M., Friedrich, T., & Lindauer, M. (2017). Improving local search in a minimum vertex cover solver for classes of networks. in 2017 IEEE Congress on Evolutionary Computation (CEC): Proceedings (S. 1704-1711). Institute of Electrical and Electronics Engineers Inc..
2016
Al-Khatib, K., Wachsmuth, H., Kiesel, J., Hagen, M., & Stein, B. (2016). A News Editorial Corpus for Mining Argumentation Strategies. in Y. Matsumoto, & R. Prasad (Hrsg.), Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers (S. 3433-3443). Association for Computational Linguistics (ACL).
Al-Khatib, K., Wachsmuth, H., Hagen, M., Köhler, J., & Stein, B. (2016). Cross-Domain Mining of Argumentative Text through Distant Supervision. in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (S. 1395-1404). Association for Computational Linguistics (ACL).
Bischl, B., Kerschke, P., Kotthoff, L., Lindauer, M., Malitsky, Y., Fréchette, A., Hoos, H., Hutter, F., Leyton-Brown, K., Tierney, K., & Vanschoren, J. (2016). ASlib: A benchmark library for algorithm selection. Artificial intelligence, 237, 41-58.
Lindauer, M., Bergdoll, R. D., & Hutter, F. (2016). An Empirical Study of Per-instance Algorithm Scheduling. in P. Festa, M. Sellmann, & J. Vanschoren (Hrsg.), Learning and Intelligent Optimization (S. 253-259). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 10079 LNCS). Springer Verlag.
Lindauer, M., Hoos, H., Leyton-Brown, K., & Schaub, T. (2016). Automatic construction of parallel portfolios via algorithm configuration. Artificial intelligence, 244, 272-290.
Manthey, N., & Lindauer, M. (2016). SpyBug: Automated Bug Detection in the Configuration Space of SAT Solvers. in D. Le Berre, & N. Creignou (Hrsg.), Theory and Applications of Satisfiability Testing – SAT 2016 (S. 554-561). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 9710). Springer Verlag.
Wachsmuth, H., Al-Khatib, K., & Stein, B. (2016). Using Argument Mining to Assess the Argumentation Quality of Essays. in Y. Matsumoto, & R. Prasad (Hrsg.), Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers (S. 1680-1691). Association for Computational Linguistics (ACL).
2015
Albrecht, S. V., Beck, J. C., Buckeridge, D. L., Botea, A., Caragea, C., Chi, C. H., Damoulas, T., Dilkina, B., Eaton, E., Fazli, P., Ganzfried, S., Giles, C. L., Guillet, S., Holte, R., Hutter, F., Koch, T., Leonetti, M., Lindauer, M., Machado, M. C., ... Zheng, Y. (2015). Reports on the 2015 AAAI Workshop Series. AI magazine, 36(2), 90-101.
Falkner, S., Lindauer, M., & Hutter, F. (2015). SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers. in M. Heule, & S. Weaver (Hrsg.), Theory and Applications of Satisfiability Testing – SAT 2015 (S. 215-222). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 9340). Springer Verlag.
Hutter, F., Lindauer, M., & Malitsky, Y. (2015). Preface. in Algorithm configuration: papers presented at the Twenty-Ninth AAAI Conference on Artificial Intelligence (S. vii). (AAAI Workshop - Technical Report).
Lindauer, M., Hoos, H. H., Schaub, T., & Hutter, F. (2015). Auto folio: Algorithm configuration for algorithm selection. in Algorithm Configuration: papers presented at the Twenty-Ninth AAAI Conference on Artificial Intelligence (S. 9-15). (AAAI Workshop - Technical Report). AI Access Foundation.
Lindauer, M. T., Hoos, H., Hutter, F., & Schaub, T. (2015). AutoFolio: An Automatically Configured Algorithm Selector. Journal of Artificial Intelligence Research, 53, 745-778.
Lindauer, M., Hoos, H. H., & Hutter, F. (2015). From Sequential Algorithm Selection to Parallel Portfolio Selection. in C. Dhaenens, L. Jourdan, & M-E. Marmion (Hrsg.), Learning and Intelligent Optimization (S. 1-16). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 8994). Springer Verlag.
Wachsmuth, H., Kiesel, J., & Stein, B. (2015). Sentiment Flow – A General Model of Web Review Argumentation. in Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (S. 601-611). Association for Computational Linguistics (ACL).
Wachsmuth, H. (2015). Text Analysis Pipelines: Towards Ad-hoc Large-Scale Text Mining. (Lecture Notes in Computer Science; Band 9383). Springer Verlag.
2014
Brüseke, F., Wachsmuth, H., Engels, G., & Becker, S. (2014). PBlaman: performance blame analysis based on Palladio contracts. Concurrency and Computation: Practice and Experience, 26(12), 1975-2004.
Hoos, H., Kaminski, R., Lindauer, M., & Schaub, T. (2014). aspeed: Solver scheduling via answer set programming. Theory and Practice of Logic Programming, 15(1), 117-142.
Hoos, H., Lindauer, M., & Schaub, T. (2014). claspfolio 2: Advances in Algorithm Selection for Answer Set Programming. Theory and Practice of Logic Programming, 14(4-5), 569-585.
Hutter, F., López-Ibáñez, M., Fawcett, C., Lindauer, M., Hoos, H. H., Leyton-Brown, K., & Stützle, T. (2014). AClib: A Benchmark Library for Algorithm Configuration. in Learning and Intelligent Optimization (S. 36-40). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 8426 LNCS). Springer Verlag.
Lindauer, M. T. (2014). Algorithm Selection, Scheduling and Configuration of Boolean Constraint Solvers. [Dissertation, Universität Potsdam].
Wachsmuth, H., Trenkmann, M., Stein, B., Engels, G., & Palakarska, T. (2014). A Review Corpus for Argumentation Analysis. in A. Gelbukh (Hrsg.), Computational Linguistics and Intelligent Text Processing - Part 2: 15th International Conference, CICLing 2014, Proceedings (S. 115-127). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 8404 LNCS). Springer Verlag.
Wachsmuth, H., Trenkmann, M., Stein, B., & Engels, G. (2014). Modeling Review Argumentation for Robust Sentiment Analysis. in J. Tsujii, & J. Hajic (Hrsg.), Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers (S. 553-564). Association for Computational Linguistics (ACL).
2013
Wachsmuth, H., Rose, M., & Engels, G. (2013). Automatic pipeline construction for real-time annotation. in A. Gelbukh (Hrsg.), Computational Linguistics and Intelligent Text Processing: 14th International Conference, CICLing 2013, Proceedings (S. 38-49). (Lecture Notes in Computer Science; Band 7816). Springer.
Wachsmuth, H., Stein, B., & Engels, G. (2013). Information Extraction as a Filtering Task. in CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management (S. 2049-2058). Association for Computing Machinery (ACM).
Wachsmuth, H., Stein, B., & Engels, G. (2013). Learning Efficient Information Extraction on Heterogeneous Texts. in R. Mitkov, & J. C. Park (Hrsg.), Proceedings of the Sixth International Joint Conference on Natural Language Processing (S. 534-542). Asian Federation of Natural Language Processing.
2012
Wachsmuth, H., & Stein, B. (2012). Optimal Scheduling of Information Extraction Algorithms. in M. Kay, & C. Boitet (Hrsg.), Proceedings of COLING 2012: Posters (S. 1281-1290). Association for Computational Linguistics (ACL).
2011
Wachsmuth, H., & Bujna, K. (2011). Back to the Roots of Genres: Text Classification by Language Function. in H. Wang, & D. Yarowsky (Hrsg.), Proceedings of the 5th International Joint Conference on Natural Language Processing (S. 632-640). Association for Computational Linguistics (ACL).
Wachsmuth, H., Stein, B., & Engels, G. (2011). Constructing Efficient Information Extraction Pipelines. in CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management (S. 2237-2240). Association for Computing Machinery (ACM).
2010
Wachsmuth, H., Prettenhofer, P., & Stein, B. (2010). Efficient Statement Identification for Automatic Market Forecasting. in C-R. Huang, & D. Jurafsky (Hrsg.), Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010) (S. 1128-1136). Association for Computational Linguistics (ACL).
2007
Arens, S., Buss, A., Deck, H., Dynia, M., Fischer, M., Hagedorn, H., Isaak, P., Krieger, A., Kutylowski, J., Auf Der Heide, F. M., Nesterow, V., Ogierman, A., Schrieb, J., Stobbe, B., Storm, T., & Wachsmuth, H. (2007). Smart Teams: Simulating Large Robotic Swarms in Vast Environments. in Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment (S. 215-222)
