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2020 – today
- 2024
[c204]Lars Hillebrand, Prabhupad Pradhan, Christian Bauckhage, Rafet Sifa:
Pointer-Guided Pre-training: Infusing Large Language Models with Paragraph-Level Contextual Awareness. ECML/PKDD (4) 2024: 386-402- [i51]Lars Hillebrand, Prabhupad Pradhan, Christian Bauckhage, Rafet Sifa:
Pointer-Guided Pre-Training: Infusing Large Language Models with Paragraph-Level Contextual Awareness. CoRR abs/2406.04156 (2024) - 2023
- [j42]Christian Bauckhage, Wolfgang Förstner, Juergen Gall, Michael Möller, Alexander G. Schwing:
Preface to the Special Issue on Pattern Recognition (DAGM GCPR 2021). Int. J. Comput. Vis. 131(5): 1210 (2023) - [j41]Laura von Rüden
, Sebastian Mayer, Katharina Beckh, Bogdan Georgiev, Sven Giesselbach, Raoul Heese, Birgit Kirsch, Julius Pfrommer, Annika Pick, Rajkumar Ramamurthy, Michal Walczak, Jochen Garcke, Christian Bauckhage, Jannis Schuecker:
Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems. IEEE Trans. Knowl. Data Eng. 35(1): 614-633 (2023) - [c203]Vanessa Toborek, Moritz Busch, Malte Boßert, Christian Bauckhage, Pascal Welke:
A New Aligned Simple German Corpus. ACL (1) 2023: 11393-11412 - [c202]Tobias Deußer, David Leonhard, Lars Hillebrand, Armin Berger, Mohamed Khaled, Sarah Heiden, Tim Dilmaghani Khameneh, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa:
Uncovering Inconsistencies and Contradictions in Financial Reports using Large Language Models. IEEE Big Data 2023: 2814-2822 - [c201]Armin Berger, Lars Hillebrand, David Leonhard, Tobias Deußer, Thiago Bell Felix De Oliveira, Tim Dilmaghani Khameneh, Mohamed Khaled, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa:
Towards Automated Regulatory Compliance Verification in Financial Auditing with Large Language Models. IEEE Big Data 2023: 4626-4635 - [c200]Lars Hillebrand, Armin Berger, Tobias Deußer, Tim Dilmaghani Khameneh, Mohamed Khaled, Bernd Kliem, Rüdiger Loitz, Maren Pielka, David Leonhard, Christian Bauckhage, Rafet Sifa:
Improving Zero-Shot Text Matching for Financial Auditing with Large Language Models. DocEng 2023: 9:1-9:4 - [c199]Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kianté Brantley, Jack Hessel, Rafet Sifa, Christian Bauckhage, Hannaneh Hajishirzi, Yejin Choi:
Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization. ICLR 2023 - [c198]Tobias Deußer, Cong Zhao, Wolfgang Krämer, David Leonhard, Christian Bauckhage, Rafet Sifa:
Controlled Randomness Improves the Performance of Transformer Models. ICMLA 2023: 1805-1810 - [c197]Laura von Rüden, Jochen Garcke, Christian Bauckhage:
How Does Knowledge Injection Help in Informed Machine Learning? IJCNN 2023: 1-8 - [c196]Tobias Deußer, Maren Pielka, Lisa Pucknat, Basil Jacob, Tim Dilmaghani Khameneh, Mahdis Nourimand, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa:
Contradiction Detection in Financial Reports. NLDL 2023 - [c195]Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke:
An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning. ECML/PKDD (3) 2023: 462-478 - [i50]Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke:
An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning. CoRR abs/2306.15786 (2023) - [i49]Lars Hillebrand, Armin Berger, Tobias Deußer, Tim Dilmaghani Khameneh, Mohamed Khaled, Bernd Kliem, Rüdiger Loitz, Maren Pielka, David Leonhard, Christian Bauckhage, Rafet Sifa:
Improving Zero-Shot Text Matching for Financial Auditing with Large Language Models. CoRR abs/2308.06111 (2023) - [i48]Tobias Deußer, Lars Hillebrand, Christian Bauckhage, Rafet Sifa:
Informed Named Entity Recognition Decoding for Generative Language Models. CoRR abs/2308.07791 (2023) - [i47]Tobias Deußer, Cong Zhao, Wolfgang Krämer, David Leonhard, Christian Bauckhage, Rafet Sifa:
Controlled Randomness Improves the Performance of Transformer Models. CoRR abs/2310.13526 (2023) - [i46]Maurice Günder, Facundo Ramón Ispizua Yamati, Abel Andree Barreto Alcántara, Anne-Katrin Mahlein, Rafet Sifa, Christian Bauckhage:
SugarViT - Multi-objective Regression of UAV Images with Vision Transformers and Deep Label Distribution Learning Demonstrated on Disease Severity Prediction in Sugar Beet. CoRR abs/2311.03076 (2023) - [i45]Maurice Günder, Sneha Banerjee, Rafet Sifa, Christian Bauckhage:
Model-agnostic Body Part Relevance Assessment for Pedestrian Detection. CoRR abs/2311.15679 (2023) - 2022
- [j40]David Biesner, Rajkumar Ramamurthy, Robin Stenzel, Max Lübbering, Lars Patrick Hillebrand, Anna Ladi, Maren Pielka, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa:
Anonymization of German financial documents using neural network-based language models with contextual word representations. Int. J. Data Sci. Anal. 13(2): 151-161 (2022) - [j39]Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa:
Bounding open space risk with decoupling autoencoders in open set recognition. Int. J. Data Sci. Anal. 14(4): 351-373 (2022) - [j38]Eldar Sultanow, Christian Bauckhage, Christian Knopf, Nico Piatkowski:
Sicherheit von Quantum Machine Learning. Wirtschaftsinformatik Manag. 14(2): 144-152 (2022) - [c194]Lars Patrick Hillebrand, Tobias Deußer, Tim Dilmaghani Khameneh, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa:
Towards automating Numerical Consistency Checks in Financial Reports. IEEE Big Data 2022: 5915-5924 - [c193]Clayton Leroy Chapman, Lars Patrick Hillebrand, Marc Robin Stenzel, Tobias Deußer, David Biesner, Christian Bauckhage, Rafet Sifa:
Towards Generating Financial Reports from Tabular Data Using Transformers. CD-MAKE 2022: 221-232 - [c192]Lukas Franken, Bogdan Georgiev, Sascha Mücke, Moritz Wolter, Raoul Heese, Christian Bauckhage, Nico Piatkowski:
Quantum Circuit Evolution on NISQ Devices. CEC 2022: 1-8 - [c191]Nico Piatkowski, Thore Gerlach, Romain Hugues, Rafet Sifa, Christian Bauckhage, Frédéric Barbaresco:
Towards Bundle Adjustment for Satellite Imaging via Quantum Machine Learning. FUSION 2022: 1-8 - [c190]Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa:
From Open Set Recognition Towards Robust Multi-class Classification. ICANN (3) 2022: 643-655 - [c189]David Biesner, Thore Gerlach, Christian Bauckhage, Bernd Kliem, Rafet Sifa:
Solving Subset Sum Problems using Quantum Inspired Optimization Algorithms with Applications in Auditing and Financial Data Analysis. ICMLA 2022: 903-908 - [c188]Tobias Deußer, Syed Musharraf Ali, Lars Patrick Hillebrand, Desiana Nurchalifah, Basil Jacob, Christian Bauckhage, Rafet Sifa:
KPI-EDGAR: A Novel Dataset and Accompanying Metric for Relation Extraction from Financial Documents. ICMLA 2022: 1654-1659 - [c187]Lars Patrick Hillebrand, Tobias Deußer, Tim Dilmaghani Khameneh, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa:
KPI-BERT: A Joint Named Entity Recognition and Relation Extraction Model for Financial Reports. ICPR 2022: 606-612 - [c186]Malik Amir, Christian Bauckhage, Alina M. Chircu, Christian Czarnecki, Christian Knopf, Nico Piatkowski, Eldar Sultanow:
What can we expect from Quantum (Digital) Twins? Wirtschaftsinformatik 2022 - [i44]Maurice Günder, Facundo Ramón Ispizua Yamati, Jana Kierdorf, Ribana Roscher, Anne-Katrin Mahlein, Christian Bauckhage:
Agricultural Plant Cataloging and Establishment of a Data Framework from UAV-based Crop Images by Computer Vision. CoRR abs/2201.02885 (2022) - [i43]Christian Bauckhage, Thore Gerlach, Nico Piatkowski:
QUBOs for Sorting Lists and Building Trees. CoRR abs/2203.08815 (2022) - [i42]Nico Piatkowski, Thore Gerlach, Romain Hugues, Rafet Sifa, Christian Bauckhage, Frédéric Barbaresco:
Towards Bundle Adjustment for Satellite Imaging via Quantum Machine Learning. CoRR abs/2204.11133 (2022) - [i41]Laura von Rüden, Sebastian Houben, Kostadin Cvejoski, Christian Bauckhage, Nico Piatkowski:
Informed Pre-Training on Prior Knowledge. CoRR abs/2205.11433 (2022) - [i40]Barry D. Reese, Marek Kowalik, Christian Metzl, Christian Bauckhage, Eldar Sultanow:
Predict better with less training data using a QNN. CoRR abs/2206.03960 (2022) - [i39]Lars Patrick Hillebrand, Tobias Deußer, Tim Dilmaghani Khameneh, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa:
KPI-BERT: A Joint Named Entity Recognition and Relation Extraction Model for Financial Reports. CoRR abs/2208.02140 (2022) - [i38]Christian Bauckhage, Helen Schneider, Benjamin Wulff, Rafet Sifa:
Gradient Flows for L2 Support Vector Machine Training. CoRR abs/2208.04365 (2022) - [i37]Vanessa Toborek, Moritz Busch, Malte Boßert, Christian Bauckhage, Pascal Welke:
A New Aligned Simple German Corpus. CoRR abs/2209.01106 (2022) - [i36]Maurice Günder, Nico Piatkowski, Christian Bauckhage:
Full Kullback-Leibler-Divergence Loss for Hyperparameter-free Label Distribution Learning. CoRR abs/2209.02055 (2022) - [i35]Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kianté Brantley, Jack Hessel, Rafet Sifa, Christian Bauckhage, Hannaneh Hajishirzi, Yejin Choi:
Is Reinforcement Learning (Not) for Natural Language Processing?: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization. CoRR abs/2210.01241 (2022) - [i34]Tobias Deußer, Syed Musharraf Ali, Lars Patrick Hillebrand, Desiana Nurchalifah, Basil Jacob, Christian Bauckhage, Rafet Sifa:
KPI-EDGAR: A Novel Dataset and Accompanying Metric for Relation Extraction from Financial Documents. CoRR abs/2210.09163 (2022) - [i33]Lars Patrick Hillebrand, Tobias Deußer, Tim Dilmaghani Khameneh, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa:
Towards automating Numerical Consistency Checks in Financial Reports. CoRR abs/2211.06112 (2022) - 2021
- [j37]Maurice Günder, Nico Piatkowski, Laura von Rüden, Rafet Sifa, Christian Bauckhage:
Towards Intelligent Food Waste Prevention: An Approach Using Scalable and Flexible Harvest Schedule Optimization With Evolutionary Algorithms. IEEE Access 9: 169044-169055 (2021) - [j36]Lars Patrick Hillebrand, David Biesner, Christian Bauckhage, Rafet Sifa:
Interpretable Topic Extraction and Word Embedding Learning Using Non-Negative Tensor DEDICOM. Mach. Learn. Knowl. Extr. 3(1): 123-167 (2021) - [c185]César Ojeda, Kostadin Cvejoski, Bogdan Georgiev, Christian Bauckhage, Jannis Schuecker, Ramsés J. Sánchez:
Learning Deep Generative Models for Queuing Systems. AAAI 2021: 9214-9222 - [c184]Rajkumar Ramamurthy, Maren Pielka, Robin Stenzel, Christian Bauckhage, Rafet Sifa, Tim Dilmaghani Khameneh, Ulrich Warning, Bernd Kliem, Rüdiger Loitz:
ALiBERT: improved automated list inspection (ALI) with BERT. DocEng 2021: 20:1-20:4 - [c183]Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa:
Decoupling Autoencoders for Robust One-vs-Rest Classification. DSAA 2021: 1-10 - [c182]Max Lübbering, Maren Pielka, Kajaree Das, Michael Gebauer, Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa:
Toxicity Detection in Online Comments with Limited Data: A Comparative Analysis. ESANN 2021 - [c181]Rhys Agombar, Christian Bauckhage, Max Lübbering, Rafet Sifa:
An Optimization for Convolutional Network Layers Using the Viola-Jones Framework and Ternary Weight Networks. LION 2021: 1-6 - [c180]Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Maren Pielka, Christian Bauckhage, Rafet Sifa:
Utilizing Representation Learning for Robust Text Classification Under Datasetshift. LWDA 2021: 157-162 - [c179]Rajkumar Ramamurthy, Max Lübbering, Thiago Bell, Michael Gebauer, Bilge Ulusay, Daniel Uedelhoven, Tim Dilmaghani Khameneh, Rüdiger Loitz, Maren Pielka, Christian Bauckhage, Rafet Sifa:
Automatic Indexing of Financial Documents via Information Extraction. SSCI 2021: 1-5 - [e1]Christian Bauckhage, Juergen Gall, Alexander G. Schwing:
Pattern Recognition - 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 - October 1, 2021, Proceedings. Lecture Notes in Computer Science 13024, Springer 2021, ISBN 978-3-030-92658-8 [contents] - [i32]Laura von Rüden, Tim Wirtz, Fabian Hüger, Jan David Schneider, Nico Piatkowski, Christian Bauckhage:
Street-Map Based Validation of Semantic Segmentation in Autonomous Driving. CoRR abs/2104.07538 (2021) - [i31]Kostadin Cvejoski, Ramsés J. Sánchez, Christian Bauckhage, César Ojeda:
Dynamic Review-based Recommenders. CoRR abs/2110.14747 (2021) - [i30]Maurice Günder, Nico Piatkowski, Laura von Rüden, Rafet Sifa, Christian Bauckhage:
Evolutionary Hierarchical Harvest Schedule Optimization for Food Waste Prevention. CoRR abs/2112.10712 (2021) - 2020
- [j35]Rafet Sifa, Raheel Yawar, Rajkumar Ramamurthy, Christian Bauckhage, Kristian Kersting:
Matrix- and Tensor Factorization for Game Content Recommendation. Künstliche Intell. 34(1): 57-67 (2020) - [c178]Lars Patrick Hillebrand, David Biesner, Christian Bauckhage, Rafet Sifa:
Interpretable Topic Extraction and Word Embedding Learning Using Row-Stochastic DEDICOM. CD-MAKE 2020: 401-422 - [c177]Christian Bauckhage, Michael Bortz, Rafet Sifa:
Shells within Minimum Enclosing Balls. DSAA 2020: 178-187 - [c176]Max Lübbering, Rajkumar Ramamurthy, Michael Gebauer, Thiago Bell, Rafet Sifa, Christian Bauckhage:
From Imbalanced Classification to Supervised Outlier Detection Problems: Adversarially Trained Auto Encoders. ICANN (1) 2020: 27-38 - [c175]Christian Bauckhage, Rajkumar Ramamurthy, Rafet Sifa:
Hopfield Networks for Vector Quantization. ICANN (2) 2020: 192-203 - [c174]Rajkumar Ramamurthy, Rafet Sifa, Max Lübbering, Christian Bauckhage:
Guided Reinforcement Learning via Sequence Learning. ICANN (2) 2020: 335-345 - [c173]Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Rafet Sifa, Christian Bauckhage:
Supervised Autoencoder Variants for End to End Anomaly Detection. ICPR Workshops (2) 2020: 566-581 - [c172]Pascal Welke, Fouad Alkhoury, Christian Bauckhage, Stefan Wrobel:
Decision Snippet Features. ICPR 2020: 4260-4267 - [c171]César Ojeda, Ramsés J. Sánchez, Kostadin Cvejoski, Jannis Schücker, Christian Bauckhage, Bogdan Georgiev:
Auto Encoding Explanatory Examples with Stochastic Paths. ICPR 2020: 6219-6226 - [c170]César Ojeda, Bogdan Georgiev, Kostadin Cvejoski, Jannis Schücker, Christian Bauckhage, Ramsés J. Sánchez:
Switching Dynamical Systems with Deep Neural Networks. ICPR 2020: 6305-6312 - [c169]Maren Pielka, Rafet Sifa, Lars Patrick Hillebrand, David Biesner, Rajkumar Ramamurthy, Anna Ladi, Christian Bauckhage:
Tackling Contradiction Detection in German Using Machine Translation and End-to-End Recurrent Neural Networks. ICPR 2020: 6696-6701 - [c168]Laura von Rüden, Tim Wirtz, Fabian Hüger, Jan David Schneider, Nico Piatkowski, Christian Bauckhage:
Street-Map Based Validation of Semantic Segmentation in Autonomous Driving. ICPR 2020: 10203-10210 - [c167]Laura von Rüden, Sebastian Mayer, Rafet Sifa, Christian Bauckhage, Jochen Garcke:
Combining Machine Learning and Simulation to a Hybrid Modelling Approach: Current and Future Directions. IDA 2020: 548-560 - [c166]Christian Bauckhage, Ramsés J. Sánchez, Rafet Sifa:
Problem Solving with Hopfield Networks and Adiabatic Quantum Computing. IJCNN 2020: 1-6 - [c165]Kostadin Cvejoski, Ramsés J. Sánchez, Bogdan Georgiev, Christian Bauckhage, César Ojeda:
Recurrent Point Review Models. IJCNN 2020: 1-8 - [c164]Rajkumar Ramamurthy, Rafet Sifa, Max Lübbering, Christian Bauckhage:
Novelty-Guided Reinforcement Learning via Encoded Behaviors. IJCNN 2020: 1-8 - [c163]Christian Bauckhage, Rafet Sifa, Dirk Hecker:
tanh Neurons Are Bayesian Decision Makers. IntelliSys (3) 2020: 703-707 - [c162]Rafet Sifa, Christian Bauckhage:
Novelty Discovery with Kernel Minimum Enclosing Balls. LION 2020: 414-420 - [c161]Christian Bauckhage, Rafet Sifa, Stefan Wrobel:
Adiabatic Quantum Computing for Max-Sum Diversification. SDM 2020: 343-351 - [p7]Christian Bauckhage, Wolfgang Hübner, Ronny Hug, Gerhard Paaß, Stefan Rüping:
Grundlagen des Maschinellen Lernens. Handbuch der Künstlichen Intelligenz 2020: 429-508 - [p6]Christian Bauckhage, Wolfgang Hübner, Ronny Hug, Gerhard Paaß:
Tiefe neuronale Netze. Handbuch der Künstlichen Intelligenz 2020: 509-570 - [p5]Christian Bauckhage, Johannes Fürnkranz, Gerhard Paaß:
Vertrauenswürdiges, transparentes und robustesMaschinelles Lernen. Handbuch der Künstlichen Intelligenz 2020: 571-600 - [i29]Tiansi Dong, Chengjiang Li, Christian Bauckhage, Juanzi Li, Stefan Wrobel, Armin B. Cremers:
Learning Syllogism with Euler Neural-Networks. CoRR abs/2007.07320 (2020) - [i28]Laura von Rüden, Tim Wirtz, Fabian Hüger, Jan David Schneider, Christian Bauckhage:
Towards Map-Based Validation of Semantic Segmentation Masks. CoRR abs/2011.08008 (2020) - [i27]Rajkumar Ramamurthy, Rafet Sifa, Christian Bauckhage:
NLPGym - A toolkit for evaluating RL agents on Natural Language Processing Tasks. CoRR abs/2011.08272 (2020) - [i26]Kostadin Cvejoski, Ramsés J. Sánchez, Bogdan Georgiev, Christian Bauckhage, César Ojeda:
Recurrent Point Review Models. CoRR abs/2012.05684 (2020) - [i25]Lukas Franken, Bogdan Georgiev, Sascha Mücke, Moritz Wolter, Nico Piatkowski, Christian Bauckhage:
Gradient-free quantum optimization on NISQ devices. CoRR abs/2012.13453 (2020)
2010 – 2019
- 2019
- [j34]Daniel Speicher, Daniel Dong, Olaf Cremers, Christian Bauckhage, Armin B. Cremers:
Notes on the Code Quality Culture on Jupyter (Notebooks). Softwaretechnik-Trends 39(2): 15-16 (2019) - [c160]Tiansi Dong, Zhigang Wang, Juanzi Li, Christian Bauckhage, Armin B. Cremers:
Triple Classification Using Regions and Fine-Grained Entity Typing. AAAI 2019: 77-85 - [c159]Eduardo Brito, Rafet Sifa, Christian Bauckhage:
Two Attempts to Predict Author Gender in Cross-Genre Settings in Dutch. GxG@CLIN 2019: 22-29 - [c158]Eduardo Brito, Rafet Sifa, Christian Bauckhage, Rüdiger Loitz, Uwe Lohmeier, Christin Pünt:
A Hybrid AI Tool to Extract Key Performance Indicators from Financial Reports for Benchmarking. DocEng 2019: 36:1-36:4 - [c157]Rafet Sifa, Anna Ladi, Maren Pielka, Rajkumar Ramamurthy, Lars Patrick Hillebrand, Birgit Kirsch, David Biesner, Robin Stenzel, Thiago Bell, Max Lübbering, Ulrich Nütten, Christian Bauckhage, Ulrich Warning, Benedikt Fürst, Tim Dilmaghani Khameneh, Daniel Thom, Ilgar Huseynov, Roland Kahlert, Jennifer Schlums, Hisham Ismail, Bernd Kliem, Rüdiger Loitz:
Towards Automated Auditing with Machine Learning. DocEng 2019: 41:1-41:4 - [c156]Christian Bauckhage, Rafet Sifa:
Joint Selection of Central and Extremal Prototypes Based on Kernel Minimum Enclosing Balls. DSAA 2019: 252-259 - [c155]Rajkumar Ramamurthy, Robin Stenzel, Rafet Sifa, Anna Ladi, Christian Bauckhage:
Echo State Networks for Named Entity Recognition. ICANN (Workshop) 2019: 110-120 - [c154]Christian Bauckhage, Rafet Sifa, Tiansi Dong:
Prototypes Within Minimum Enclosing Balls. ICANN (Workshop) 2019: 365-376 - [c153]Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa, Jannis Schücker, Stefan Wrobel:
Leveraging Domain Knowledge for Reinforcement Learning Using MMC Architectures. ICANN (2) 2019: 595-607 - [c152]Tiansi Dong, Christian Bauckhage, Hailong Jin, Juanzi Li, Olaf Cremers, Daniel Speicher, Armin B. Cremers, Jörg Zimmermann:
Imposing Category Trees Onto Word-Embeddings Using A Geometric Construction. ICLR (Poster) 2019 - [c151]César Ali Marin Ojeda, Kostadin Cvejoski, Rafet Sifa, Jannis Schücker, Christian Bauckhage:
Patterns and Outliers in Temporal Point Processes. IntelliSys (1) 2019: 507-526 - [c150]Maren Pielka, Rafet Sifa, Rajkumar Ramamurthy, César Ojeda, Christian Bauckhage:
A Community Detection Based Approach for Exploring Patterns in Player Reviews. IntelliSys (1) 2019: 553-565 - [c149]Christian Bauckhage, Nico Piatkowski, Rafet Sifa, Dirk Hecker, Stefan Wrobel:
A QUBO Formulation of the k-Medoids Problem. LWDA 2019: 54-63 - [c148]Christian Bauckhage, Rafet Sifa, Dirk Hecker, Stefan Wrobel:
Max-Sum Dispersion via Quantum Annealing. LWDA 2019: 64-68 - [c147]Eduardo Brito, Bogdan Georgiev, Daniel Domingo-Fernández, Charles Tapley Hoyt, Christian Bauckhage:
RatVec: A General Approach for Low-dimensional Distributed Vector Representations via Rational Kernels. LWDA 2019: 74-78 - [c146]Vishwani Gupta, Sven Giesselbach, Stefan Rüping, Christian Bauckhage:
Improving Word Embeddings Using Kernel PCA. RepL4NLP@ACL 2019: 200-208 - [c145]Rafet Sifa, Maren Pielka, Rajkumar Ramamurthy, Anna Ladi, Lars Patrick Hillebrand, Christian Bauckhage:
Towards Contradiction Detection in German: a Translation-Driven Approach. SSCI 2019: 2497-2505 - [i24]Laura von Rüden, Sebastian Mayer, Jochen Garcke, Christian Bauckhage, Jannis Schücker:
Informed Machine Learning - Towards a Taxonomy of Explicit Integration of Knowledge into Machine Learning. CoRR abs/1903.12394 (2019) - [i23]César Ojeda, Kostadin Cvejosky, Ramsés J. Sánchez, Jannis Schücker, Bogdan Georgiev, Christian Bauckhage:
Recurrent Adversarial Service Times. CoRR abs/1906.09808 (2019) - [i22]Eduardo Brito, Max Lübbering, David Biesner, Lars Patrick Hillebrand, Christian Bauckhage:
Towards Supervised Extractive Text Summarization via RNN-based Sequence Classification. CoRR abs/1911.06121 (2019) - [i21]Kostadin Cvejoski, Ramsés J. Sánchez, Bogdan Georgiev, Jannis Schuecker, Christian Bauckhage, César Ojeda:
Recurrent Point Processes for Dynamic Review Models. CoRR abs/1912.04132 (2019) - [i20]Christian Bauckhage, Daniel Schulz, Dirk Hecker:
Informed Machine Learning for Industry. ERCIM News 2019(116) (2019) - 2018
- [j33]Daniel Speicher, Tiansi Dong, Christian Bauckhage, Armin B. Cremers:
Growing Executable Code-Quality-Knowledge Organically. Softwaretechnik-Trends 38(2): 61-62 (2018) - [c144]Rafet Sifa, Raheel Yawar, Rajkumar Ramamurthy, Christian Bauckhage:
Matrix and Tensor Factorization Based Game Content Recommender Systems: A Bottom-Up Architecture and a Comparative Online Evaluation. AIIDE 2018: 102-108 - [c143]Rafet Sifa, Julian Runge, Christian Bauckhage, Daniel Klapper:
Customer Lifetime Value Prediction in Non-Contractual Freemium Settings: Chasing High-Value Users Using Deep Neural Networks and SMOTE. HICSS 2018: 1-10 - [c142]Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa, Stefan Wrobel:
Policy Learning Using SPSA. ICANN (3) 2018: 3-12 - [c141]Rafet Sifa, Daniel Paurat, Daniel Trabold, Christian Bauckhage:
Simple Recurrent Neural Networks for Support Vector Machine Training. ICANN (3) 2018: 13-22 - [c140]Benjamin Wulff, Jannis Schücker, Christian Bauckhage:
SPSA for Layer-Wise Training of Deep Networks. ICANN (3) 2018: 564-573 - [c139]Christian Bauckhage, César Ojeda, Rafet Sifa, Stefan Wrobel:
Adiabatic Quantum Computing for Kernel k=2 Means Clustering. LWDA 2018: 21-32 - [c138]Christian Bauckhage, César Ojeda, Jannis Schücker, Rafet Sifa, Stefan Wrobel:
Informed Machine Learning Through Functional Composition. LWDA 2018: 33-37 - [i19]Patrick Schramowski, Christian Bauckhage, Kristian Kersting:
Neural Conditional Gradients. CoRR abs/1803.04300 (2018) - 2017
- [c137]Rafet Sifa, Christian Bauckhage:
Online k-Maxoids Clustering. DSAA 2017: 667-675 - [c136]Christian Bauckhage, Eduardo Brito, Kostadin Cvejoski, César Ojeda, Rafet Sifa, Stefan Wrobel:
Ising Models for Binary Clustering via Adiabatic Quantum Computing. EMMCVPR 2017: 3-17 - [c135]