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Number of items at this level: 257.

A

Abbaszadeh, Sadegh

and Hüllermeier, Eyke

(December 2021): Machine Learning With the Sugeno Integral: The Case of Binary Classification. In: IEEE Transactions on Fuzzy Systems, No. 12: pp. 3723-3733

Abiteboul, Serge; Arenas, Marcelo; Barceló, Pablo; Bienvenu, Meghyn; Calvanese, Diego; David, Claire; Hull, Richard; Hüllermeier, Eyke

; Kimelfeld, Benny; Libkin, Leonid; Martens, Wim; Milo, Tova; Murlak, Filip; Neven, Frank; Ortiz, Magdalena; Schwentick, Thomas; Stoyanovich, Julia; Su, Jianwen; Suciu, Dan; Vianu, Victor and Yi, Ke (December 2016): Research Directions for Principles of Data Management (Abridged). In: SIGMOD Record, Vol. 45, No. 4: 5–17

Abiteboul, Serge; Arenas, Marcelo; Barceló, Pablo; Bienvenu, Meghyn; Calvanese, Diego; David, Claire; Hull, Richard; Hüllermeier, Eyke

; Kimelfeld, Benny; Libkin, Leonid; Martens, Wim; Milo, Tova; Murlak, Filip; Neven, Frank; Ortiz, Magdalena; Schwentick, Thomas; Stoyanovich, Julia; Su, Jianwen; Suciu, Dan; Vianu, Victor and Yi, Ke (April 2018): Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151). In: Dagstuhl Manifestos, Vol. 7, No. 1: pp. 1-29

Adel, Heike and Schütze, Hinrich (September 2019): Type-aware Convolutional Neural Networks for Slot Filling. In: Journal of Artificial Intelligence Research, Vol. 66: pp. 297-339 [PDF, 496kB]

Ahmadi Fahandar, Mohsen and Hüllermeier, Eyke (April 2021): Analogical Embedding for Analogy-Based Learning to Rank. Advances in Intelligent Data Analysis XIX. IDA 2021, Porto, Portugal, April 26-28, 2021. In: Advances in Intelligent Data Analysis XIX. Vol. 12695. Vol. 12695. Cham: Springer. pp. 76-88

Allam, Ahmed

; Feuerriegel, Stefan

; Rebhan, Michael

and Krauthammer, Michael

(2021): Analyzing Patient Trajectories With Artificial Intelligence. In: Journal of Medical Internet Research, Vol. 23, No. 12, e29812 [PDF, 446kB]

Allioli, Joseph Franz (1830): Ueber die Aufgabe des Lebens auf Hochschulen in Bezug auf Wissenschaft und Gesittung. München [PDF, 11MB]

Aschersleben, G.; Gstalter, Herbert; Kaiser, F.; Strube, V. and Zang, B. (1989): Prototyping als Verfahren zur Software-Entwicklung. Literaturanalyse und Expertengespräche. In: Zeitschrift für Arbeitswissenschaft, No. 43: pp. 42-47 [PDF, 4MB]

B

Banholzer, Nicolas; Feuerriegel, Stefan

and Vach, Werner (2022): Estimating and explaining cross-country variation in the effectiveness of non-pharmaceutical interventions during COVID-19. In: Scientific Reports, Vol. 12, No. 1, 7526 [PDF, 1MB]

Banholzer, Nicolas

; Lison, Adrian; Özcelik, Dennis; Stadler, Tanja; Feuerriegel, Stefan

and Vach, Werner (2022): The methodologies to assess the effectiveness of non-pharmaceutical interventions during COVID-19: a systematic review. In: European Journal of Epidemiology, Vol. 37, No. 10: pp. 1003-1024 [PDF, 1MB]

Bayer, Hieronymus (1831): Rede an die Studirenden der Ludwigs-Maximilians-Universität in München. München: Weber. [PDF, 6MB]

Behmel, Andreas; Kienzl, Thomas and Höhl, Wolfgang (11. September 2014): [DEMO] MRI Design Review System. A Mixed Reality Interactive Design Review System for Architecture, Serious Games and Engineering using Game Engines, Standard Software, a Tablet Computer and Natural Interfaces. ISMAR 2014 International Symposium on Mixed and Augmented Reality, Technische Universität München, 08. - 12. September 2014. In: [PDF, 257kB]

Bengs, Viktor

and Hüllermeier, Eyke

(16. November 2022): Multi-armed bandits with censored consumption of resources. In: Machine Learning, Vol. 112, No. 2: pp. 217-240

Bengs, Viktor

; Hüllermeier, Eyke

and Waegeman, Willem

(2023): On Second-Order Scoring Rules for Epistemic Uncertainty Quantification. 40th International Conference on Machine Learning (ICML 2023), Hawaii, USA, 23-29 July, 2023. In: Krause, Andreas; Brunskill, Emma; Cho, Kyunghyun; Engelhardt, Barbara; Sabato, Sivan and Scarlett, Jonathan (eds.) : Proceedings of the 40th International Conference on Machine Learning. Vol. 202. PMLR. pp. 2078-2091

Bengs, Viktor; Busa-Fekete, Róbert; Mesaoudi-Paul, Adil El and Hüllermeier, Eyke

(January 2021): Preference-based Online Learning with Dueling Bandits: A Survey. In: Journal of Machine Learning Research, Vol. 22, No. 7: pp. 1-108

Bengs, Viktor and Hüllermeier, Eyke

(July 2020): Preselection Bandits. 37th International Conference on Machine Learning, Virtual, July 12-18 2020. In: III, Hal Daumé and Singh, Aarti (eds.) : Proceedings of the 37th International Conference on Machine Learning. Vol. 119. PMLR. pp. 778-787

Bengs, Viktor

; Hüllermeier, Eyke

and Waegeman, Willem

(28. November 2022): Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation. Advances in Neural Information Processing Systems, New Orleans, USA, 28 November - 9 December 2022. In: Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle and Cho, Kyunghyun (eds.) :

Bengs, Viktor; Saha, Aadirupa and Hüllermeier, Eyke

(July 2022): Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models. 39th International Conference on Machine Learning, Baltimore, MD, USA, July 17-23 2022. In: Chaudhuri, Kamalika; Jegelka, Stefanie; Song, Le; Szepesvari, Csaba; Niu, Gang and Sabato, Sivan (eds.) : Proceedings of the 39th International Conference on Machine Learning. Vol. 162. PMLR. pp. 1764-1786

Benk, Michaela; Weibel, Raphael P.; Feuerriegel, Stefan

and Ferrario, Andrea (2022): "Is It My Turn?" Assessing Teamwork and Taskwork in Collaborative Immersive Analytics. In: Proceedings of the ACM on Human-Computer Interaction, Vol. 6, No. CSCW2: pp. 1-23

Berger, Benedikt

; Niedernhuber, Tanja

; Hess, Thomas

and Engländer, Armin (June 2021): Nutzung digitaler Tools in Lehrveranstaltungen. München [PDF, 6MB]

Bernhart, Elias

(18. January 2018): Orientierung zum Datenmanagement und Hinweise für die Erstellung eines Datenmanagementplans für qualitative Daten an der LMU München. [PDF, 1MB]

Biagini, Francesca (2017): Quantitative Network Science (QNetS). CAS Concepts, Vol. 5. München: Ludwig-Maximilians-Universität. [PDF, 849kB]

Blattmann, Andreas; Milbich, Timo; Dorkenwald, Michael and Ommer, Björn

(2021): Behavior-Driven Synthesis of Human Dynamics. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, 20-25 June 2021. In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). New York: IEEE. pp. 12231-12241

Blümlein, Theresa; Persson, Joel and Feuerriegel, Stefan

(2022): Learning Optimal Dynamic Treatment Regimes Using Causal Tree Methods in Medicine. MLHC 2022, Durham, 05.08.2022-06.08.2022. In: arXiv.

Brandt, Jasmin; Schede, Elias; Haddenhorst, Björn

; Bengs, Viktor

; Hüllermeier, Eyke

and Tierney, Kevin (7. February 2023): AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration. AAAI Conference on Artificial Intelligence, Washington, DC, USA, February, 2023. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 37. pp. 12355-12363

Brandt, Jasmin; Bengs, Viktor

; Haddenhorst, Björn

and Hüllermeier, Eyke

(28. November 2022): Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget. Advances in Neural Information Processing Systems, New Orleans, USA, 28 November - 9 December 2022. In: Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle and Cho, Kyunghyun (eds.) :

Bresson, Roman; Cohen, Johanne; Hüllermeier, Eyke

; Labreuche, Christophe and Sebag, Michèle (2020): Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals. Twenty-Ninth International Joint Conference on Artificial Intelligence, Yokohama, Japan (Virtual), January 7-15, 2021. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. pp. 1984-1991

Bresson, Roman; Cohen, Johanne; Hüllermeier, Eyke

; Labreuche, Christophe and Sebag, Michèle (3. November 2021): On the Identifiability of Hierarchical Decision Models. International Conference on Principles of Knowledge Representation and Reasoning, Virtual, November 3-12, 2021. In: Proceedings of the Eighteenth International Conference on Principles of Knowledge Representation and Reasoning. pp. 151-162

Brinkhoff, Thomas; Horn, H.; Kriegel, Hans-Peter and Schneider, Ralf (1993): Eine Speicher- und Zugriffsarchitektur für effiziente Anfragebearbeitung in Geo-Datenbankensystemen. Fachtagung Datenbanksysteme in Büro, Technik und Wissenschaft, Braunschweig, 1993. In: 5. Fachtagung Datenbanksysteme in Büro, Technik und Wissenschaft (ed.) , Datenbanksysteme in Büro, Technik und Wissenschaft. Berlin: Springer. pp. 356-374 [PDF, 2MB]

Broschart, Daniel and Höhl, Wolfgang (1. April 2015): Augmented Reality in Architektur und Stadtplanung. Potenziale von Augmented Reality in Architektur und Stadtplanung. In: GIS Science, No. 1: pp. 20-29 [PDF, 847kB]

Burghardt, Manuel; Isemann, Daniel; Kattenbeck, Markus; Ludwig, Bernd and Wolff, Christian (2018): Digital Humanities an der Universität Regensburg. Geschichte – Projekte – Studiengang. In: Klinke, Harald (ed.) : #DigiCampus. Digitale Forschung und Lehre in den Geisteswissenschaften. München: Universitätsbibliothek der Ludwig-Maximilians-Universität. pp. 115-128 [PDF, 1MB]

Busa-Fekete, Róbert; Hüllermeier, Eyke

and Szörényi, Balázs (2014): Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows. 31st International Conference on Machine Learning (ICML 2014), Beijing, China, 21-26 June, 2014. In: Xing, Eric P. and Jebara, Tony (eds.) : Proceedings of the 31st International Conference on Machine Learning. Vol. 32. Bejing, China: PMLR. pp. 1071-1079

Bär, Dominik; Calderon, Fausto; Lawlor, Michael; Licklederer, Sophia; Totzauer, Manuel and Feuerriegel, Stefan

(2023): Analyzing Social Media Activities at Bellingcat. WebSci'23, Austin, 30.04.2023-01.05.2023. In: arXiv.

Bär, Dominik; Pröllochs, Nicolas and Feuerriegel, Stefan

(2022): Finding Qs: Profiling QAnon Supporters on Parler. ICWSM 2023, Limassol, 05.06.2023-08.06.2023. In: arXiv.

Bär, Dominik; Pröllochs, Nicolas and Feuerriegel, Stefan

(2023): New threats to society from free-speech social media platforms. arXiv

C

Campagner, Andrea

; Ciucci, Davide

and Hüllermeier, Eyke

(June 2020): Feature Reduction in Superset Learning Using Rough Sets and Evidence Theory. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Lisbon, Portugal, 15-19 June 2020. In: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Vol. 1237. Vol. 1237. Cham: Springer. pp. 471-484

Campagner, Andrea

; Ciucci, Davide

and Hüllermeier, Eyke

(June 2021): Rough set-based feature selection for weakly labeled data. In: International Journal of Approximate Reasoning: pp. 150-167

Campagner, Andrea

; Lienen, Julian

; Hüllermeier, Eyke

and Ciucci, Davide

(2022): Scikit-Weak: A Python Library for Weakly Supervised Machine Learning. International Joint Conference on Rough Sets, Suzhou, China, 11-14 November 2022. In: Rough Sets. Vol. 13633. Vol. 13633. Cham: Springer. pp. 57-70

Cornolti, Marco; Ferragina, Paolo; Ciaramita, Massimiliano; Rüd, Stefan and Schütze, Hinrich (December 2018): SMAPH: A Piggyback Approach for Entity-Linking in Web Queries. In: ACM Transactions on Information Systems, Vol. 37, No. 1, 13 [PDF, 1MB]

D

Dari, Simone; Kadrileev, Nikolay and Hüllermeier, Eyke

(July 2020): A Neural Network-Based Driver Gaze Classification System with Vehicle Signals. 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 19-24 July 2020. In: 2020 International Joint Conference on Neural Networks (IJCNN). pp. 1-7

Dellnitz, Michael; Hüllermeier, Eyke

; Lücke, Marvin

; Ober-Blöbaum, Sina; Offen, Christian

; Peitz, Sebastian

and Pfannschmidt, Karlson

(2023): Efficient Time-Stepping for Numerical Integration Using Reinforcement Learning. In: SIAM Journal on Scientific Computing, Vol. 45, No. 2: A579-A595

Dolata, Mateusz

; Feuerriegel, Stefan

and Schwabe, Gerhard (2022): A sociotechnical view of algorithmic fairness. In: Information Systems Journal, Vol. 32, No. 4: pp. 754-818

Dufter, Philipp; Kassner, Nora and Schütze, Hinrich (June 2021): Static Embeddings as Efficient Knowledge Bases? 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Online, June 6-11, 2021. In: Toutanova, Kristina (ed.) : Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Stroudsburg, PA: Association for Computational Linguistics. pp. 2353-2363 [PDF, 340kB]

Dufter, Philipp and Schütze, Hinrich (November 2018): A Stronger Baseline for Multilingual Word Embeddings. [PDF, 173kB]

Dufter, Philipp and Schütze, Hinrich (3. November 2019): Analytical Methods for Interpretable Ultradense Word Embeddings. UNSPECIFIED, November 3–7, 2019, Hong Kong, China [PDF, 423kB]

Dufter, Philipp and Schütze, Hinrich (November 2020): Identifying Elements Essential for BERT’s Multilinguality. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Online, 16th – 20th November 2020. In: [PDF, 863kB]

Dufter, Philipp and Schütze, Hinrich (1. May 2020): Identifying Necessary Elements for BERT’s Multilinguality. [PDF, 631kB]

Dufter, Philipp; Zhao, Mengjie; Schmitt, Martin; Fraser, Alexander and Schütze, Hinrich (July 2018): Embedding Learning Through Multilingual Concept Induction. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Melbourne, Australia, July 15-20, 2018. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Vol. 1. Association for Computational Linguistics. pp. 1520-1530 [PDF, 453kB]

E

Erhard, Florian; Doelken, Lars; Jaskiewicz, Lukasz and Zimmer, Ralf (2013): PARma: identification of microRNA target sites in AGO-PAR-CLIP data. In: Genome Biology 14:R79 [PDF, 3MB]

Ess, Hans van (2016): Zur Situation der Geisteswissenschaften heute. CAS eSeries, Vol. 13. München: Ludwig-Maximilians-Universität. [PDF, 1MB]

F

Fakesch, Jens (25. July 2016): Multi-User 3D Augmented Reality Anwendung für die gemeinsame Interaktion mit virtuellen 3D Objekten. Master Thesis, Faculty of Mathematics, Computer Science and Statistics, Ludwig-Maximilians-Universität München. [PDF, 31MB]

Feldhans, Robert; Wilke, Adrian; Heindorf, Stefan; Shaker, Mohammad Hossein; Hammer, Barbara; Ngonga Ngomo, Axel-Cyrille and Hüllermeier, Eyke

(November 2021): Drift Detection in Text Data with Document Embeddings. Intelligent Data Engineering and Automated Learning – IDEAL 2021, Manchester, United Kingdom, November 25-27, 2021. In: Intelligent Data Engineering and Automated Learning – IDEAL 2021. Vol. 13113. Vol. 13113. Cham: Springer. pp. 107-118

Feuerriegel, Stefan

; Shrestha, Yash Raj and Krogh, Georg von (2022): Bringing artificial intelligence to business management. In: Nature Machine Intelligence, Vol. 4: pp. 611-613

Fischer, Frank; Wecker, Christof and Stegmann, Karsten (October 2015): Auswirkungen digitaler Medien auf den Wissens- und Kompetenzerwerb in der Schule. [PDF, 438kB]

Frank, Markus (2018): Digital Humanities Sprachwissenschaften. Schwerpunkte bei der Entwicklung eines sprachwissenschaftlichen DH-Nebenfaches. In: Klinke, Harald (ed.) : #DigiCampus. Digitale Forschung und Lehre in den Geisteswissenschaften. München: Universitätsbibliothek der Ludwig-Maximilians-Universität. pp. 103-114 [PDF, 148kB]

Frauen, Dennis and Feuerriegel, Stefan

(2022): Estimating individual treatment effects under unobserved confounding using binary instruments. ICLR 2023, Kigali, 01.05.2023-05.05.2023. In: arXiv.

Frauen, Dennis; Hatt, Tobias; Melnychuk, Valentyn and Feuerriegel, Stefan

(2022): Estimating average causal effects from patient trajectories. AAAI-23, Washington D.C., 07.02.2023-14.02.2023. In: arXiv.

Fritz, Cornelius; Lebacher, Michael and Kauermann, Göran (2020): Tempus volat, hora fugit: A survey of tie‐oriented dynamic network models in discrete and continuous time. In: Statistica Neerlandica, Vol. 74, No. 3: pp. 275-299 [PDF, 3MB]

Fuchs, Mathias; Jiang, Xiaoyu and Anne-Laure, Boulesteix (14. January 2016): The computationally optimal test set size in simulation studies on supervised learning. Department of Statistics: Technical Reports, No.189 [PDF, 432kB]

Föll, Simon

; Lison, Adrian

; Maritsch, Martin

; Klingberg, Karsten

; Lehmann, Vera

; Züger, Thomas

; Srivastava, David

; Jegerlehner, Sabrina

; Feuerriegel, Stefan

; Fleisch, Elgar

; Exadaktylos, Aristomenis

and Wortmann, Felix

(2022): A Scalable Risk-Scoring System Based on Consumer-Grade Wearables for Inpatients With COVID-19: Statistical Analysis and Model Development. In: JMIR Formative Research, Vol. 6, No. 6, e35717 [PDF, 875kB]

Fütterer, Cornelia; Nalenz, Malte and Augustin, Thomas (11. November 2021): Discriminative Power Lasso - Incorporating Discriminative Power of Genes into Regularization-Based Variable Selection. Department of Statistics: Technical Reports, No.239 [PDF, 436kB]

G

Ganter, Manuel; Toetzke, Malte and Feuerriegel, Stefan

(2022): Mining points-of-interest data to predict urban inequality: Evidence from Germany and France. ICWSM 2022, Atlanta, 06.06.2022-09.06.2022. In: Budak, Ceren; Cha, Meeyoung and Quercia, Daniele (eds.) : Proceedings of the International AAAI Conference on Web and Social Media. Vol. 16. Palo Alto, CA: Association for the Advancement of Artificial Intelligence. 216 - 227

Gupta, Pritha

; Drees, Jan Peter

and Hüllermeier, Eyke

(2023): Automated Side-Channel Attacks using Black-Box Neural Architecture Search. 18th International Conference on Availability, Reliability and Security, Benevento, Italy, 29 August - 1 September 2023. In: Proceedings of the 18th International Conference on Availability, Reliability and Security. New York, NY, USA: Association for Computing Machinery. pp. 1-11

Gupta, Pritha

; Ramaswamy, Arunselvan

; Drees, Jan Peter

; Hüllermeier, Eyke

; Priesterjahn, Claudia

and Jager, Tibor

(February 2022): Automated Information Leakage Detection: A New Method Combining Machine Learning and Hypothesis Testing with an Application to Side-channel Detection in Cryptographic Protocols. 14th International Conference on Agents and Artificial Intelligence (ICAART 2022), Virtual, February 3-5. In: Proceedings of the 14th International Conference on Agents and Artificial Intelligence. Vol. 2. pp. 152-163

Gümüsay, Ali Aslan; Raynard, Mia; Albu, Oana; Etter, Michael and Roulet, Thomas (2022): Digital Technology and Voice: How Platforms Shape Institutional Processes Through Visibilization. In: Gegenhuber, T.; Logue, D.; Hinings, C.R.(B). and Barrett, M. (eds.) : Digital Transformation and Institutional Theory. Research in the Sociology of Organizations, Vol. 83. Bingley: Emerald. pp. 57-85 [PDF, 1MB]

H

Haas, Stefan

and Hüllermeier, Eyke

(September 2022): A Prescriptive Machine Learning Approach for Assessing Goodwill in the Automotive Domain. Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2022), Grenoble, France, 19-23 September, 2023. In: Machine Learning and Knowledge Discovery in Databases. Vol. 13718. Cham: Springer. pp. 170-184

Haas, Stefan

and Hüllermeier, Eyke

(18. September 2023): Rectifying Bias in Ordinal Observational Data Using Unimodal Label Smoothing. Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Torino, Italy, 18-22 September, 2023. In: Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track. Vol. 14174. pp. 3-18

Haddenhorst, Björn

; Bengs, Viktor; Brandt, Jasmin and Hüllermeier, Eyke

(27. July 2021): Testification of Condorcet Winners in dueling bandits. Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, Virtual, July 27-30, 2021. In: de Campos, Cassio and Maathuis, Marloes H. (eds.) : Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence. Vol. 161. PMLR. pp. 1195-1205

Haddenhorst, Björn

; Bengs, Viktor and Hüllermeier, Eyke

(7. December 2021): Identification of the Generalized Condorcet Winner in Multi-dueling Bandits. Advances in Neural Information Processing Systems, Virtual, December 7 2021. In: Ranzato, M.; Beygelzimer, A.; Dauphin, Y.; Liang, P.S. and Vaughan, J. Wortman (eds.) : Vol. 34. Curran Associates, Inc.. pp. 25904-25916

Hanselle, Jonas; Fürnkranz, Johannes and Hüllermeier, Eyke (2023): Probabilistic Scoring Lists for Interpretable Machine Learning. 26th International Conference on Discovery Science (DS 2023), Porto, Portugal, October 9-11, 2023. In: Discovery Science. Vol. 14276. Cham: Springer. pp. 189-203

Hatt, Tobias and Feuerriegel, Stefan

(2021): Estimating Average Treatment Effects via Orthogonal Regularization. CIKM: Conference on Information and Knowledge Management, Queensland, 01.11.2021-05.11.2021. In: CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management. pp. 680-689

Hatt, Tobias; Tschernutter, Daniel and Feuerriegel, Stefan

(2021): Generalizing Off-Policy Learning under Sample Selection Bias. UAI 2022, Eindhoven, 01.08.2022-05.08.2022. In: arXiv.

Hengerer, Mark Sven; Hödl-Notter, Isabella and Schön, Gerhard (2018): Squirrel. Ein innovativer Editor zur Erstellung digitaler Editionen und sein Pilotprojekt. In: Klinke, Harald (ed.) : #DigiCampus. Digitale Forschung und Lehre in den Geisteswissenschaften. München: Universitätsbibliothek der Ludwig-Maximilians-Universität. pp. 129-138 [PDF, 4MB]

Hofmann, Valentin; Pierrehumbert, Janet and Schütze, Hinrich (November 2020): DagoBERT: Generating Derivational Morphology with a Pretrained Language Model. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Online, 16. – 20. November 2020. In: [PDF, 2MB]

Hofmann, Valentin; Pierrehumbert, Janet and Schütze, Hinrich (6. July 2020): Predicting the Growth of Morphological Families from Social and Linguistic Factors. UNSPECIFIED, July 6 – 8, 2020, Seattle, USA [PDF, 2MB]

Hofmann, Valentin; Pierrehumbert, Janet B. and Schütze, Hinrich (August 2021): Dynamic Contextualized Word Embeddings. 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Online, August 2021. In: Zong, Chengqing; Xia, Fei; Li, Wenjie and Navigli, Roberto (eds.) : Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics. pp. 6970-6984 [PDF, 4MB]

Hofmann, Valentin; Pierrehumbert, Janet B. and Schütze, Hinrich (August 2021): Superbizarre Is Not Superb: Derivational Morphology Improves BERT’s Interpretation of Complex Words. 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Online, August 2021. In: Zong, Chengqing; Xia, Fei; Li, Wenjie and Navigli, Roberto (eds.) : Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). pp. 3594-3608 [PDF, 1MB]

Hofmann, Valentin; Schütze, Hinrich and Pierrehumbert, Janet (6. July 2020): A Graph Auto-encoder Model of Derivational Morphology. UNSPECIFIED, July 6 – 8, 2020, Seattle, USA [PDF, 1MB]

Hofmann, Valentin; Schütze, Hinrich and Pierrehumbert, Janet B. (May 2022): An Embarrassingly Simple Method to Mitigate Undesirable Properties of Pretrained Language Model Tokenizers. 60th Annual Meeting of the Association for Computational Linguistics, Dublin, Ireland, May 22-27, 2022. In: Muresan, Smarandakov; Nakov, Preslav and Villavicencio, Aline (eds.) : Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Stroudsburg, PA: Association for Computational Linguistics. pp. 385-393 [PDF, 480kB]

Hummler, Philipp; Naumzik, Christof and Feuerriegel, Stefan

(2022): Web Mining to Inform Locations of Charging Stations for Electric Vehicles. WWW '22: The ACM Web Conference 2022, Lyon, 25.04.2022-29.04.2022. In: Laforest, Frédérique; Troncy, Raphaël; Médini, Lionel and Herman, Ivan (eds.) : Companion Proceedings of the Web Conference 2022. New York: Association for Computing Machinery (ACM). pp. 166-170

Häuber, Chrystina (March 2015): Rome: the city of memories. Or, why and how reconstruct and visualize ancient and post-antique Rome using digital technologies? The "AIS ROMA", diachronic and phase maps of (ancient) Rome in the WWW Long version 2015, München. The International Symposium Reconstruction and the Historic City: Rome and Abroad - an interdisciplinary approach, LMU München, Deutschland, 17. - 19. Oktober 2012. In: [PDF, 8MB]

Höhl, Wolfgang (9. March 2017): Industrie 4.0 und Angewandte Interaktive Technologien (APITs). Identifizieren von Projektpartnern und interdisziplinären Synergien mit der APITs-Vernetzungsmatrix. Elemente, Aufbau und Struktur interaktiver industrieller Anwendungen für Augmented Reality, Mixed Reality und Virtual Reality. [PDF, 833kB]

Höhl, Wolfgang

(4. June 2012): Netzwerktheorie und Prozessoptimierung. In: Business + Innovation, No. 2: pp. 24-32

Höhl, Wolfgang

(16. September 2017): Open Innovation and Applied Interactive Technologies. Identifying project partners and interdisciplinary synergies with the Applied Interactive Technologies (APITs) networking matrix. ACM Symposium on Applied Perception, Brandenburg University of Technology in Cottbus, Germany, 16. - 17. September 2017. In: [PDF, 270kB]

Höhl, Wolfgang (1. January 2014): Sim Games, Simulation und industrielle Anwendungen. In: Kaiser, Markus (ed.) : Ringvorlesung Games. Retro Gaming, Gamification, Augmented Reality, Vol. 1. 1. München: Verlag Dr. Gabriele Hooffacker / MedienCampus Bayern e.V.. pp. 80-97 [PDF, 682kB]

Hüllermeier, Eyke

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Zhao, Mengjie; Mi, Fei; Wang, Yasheng; Li, Minglei; Jiang, Xin; Liu, Qun and Schütze, Hinrich (July 2022): LMTurk: Few-Shot Learners as Crowdsourcing Workers in a Language-Model-as-a-Service Framework. NAACL 2022, Seattle, United States, July 2022. In: Carpuat,, Marine; de Marneffe, Marie-Catherine and Meza Ruiz, Ivan Vladimir (eds.) : Findings of the Association for Computational Linguistics: NAACL 2022. Stroudsburg, PA: Association for Computational Linguistics (ACL). pp. 675-692 [PDF, 2MB]

Zhao, Mengjie; Dufter, Philipp; Yaghoobzadeh, Yadollah and Schütze, Hinrich (2020): Quantifying the Contextualization of Word Representations with Semantic Class Probing. In: Findings of ACL: EMNLP 2020 [PDF, 495kB]

Zhao, Mengjie and Schütze, Hinrich (28. July 2019): A Multilingual BPE Embedding Space for Universal Sentiment Lexicon Induction. UNSPECIFIED, July 28 - August 2, 2019, Florence, Italy [PDF, 544kB]

Zhao, Mengjie and Schütze, Hinrich (November 2021): Discrete and Soft Prompting for Multilingual Models. 2021 Conference on Empirical Methods in Natural Language Processing, Online and Punta Cana, Dominican Republic, November 2021. In: Moens, Marie-Francine; Huang, Xuanjing; Specia, Lucia and Yih, Scott Wen-tau (eds.) : Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Stroudsburg PA: Association for Computational Linguistics. [PDF, 383kB]

Zhao, Mengjie; Zhu, Yi; Shareghi, Ehsan; Vulic, Ivan; Reichart, Roi; Korhonen, Anna and Schütze, Hinrich (August 2021): A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters. 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Online, August 2021. In: Zong, Chengqing; Xia, Fei; Li, Wenjie and Navigli, Roberto (eds.) : Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics. pp. 5751-5767 [PDF, 737kB]

Zueger, Thomas

; Schallmoser, Simon; Kraus, Mathias; Saar-Tsechansky, Maytal; Feuerriegel, Stefan

and Stettler, Christoph (2022): Machine Learning for Predicting the Risk of Transition from Prediabetes to Diabetes. In: Diabetes Technology & Therapeutics, Vol. 24, No. 11: pp. 842-847

This list was generated on Thu Nov 30 22:55:20 2023 CET.