Rajkumar Ramamurthy

According to our database, Rajkumar Ramamurthy authored at least 29 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Practical Models for Sequential Decision Making in Natural Language Processing and Reinforcement Learning.

Rajkumar Ramamurthy

PhD thesis, 2023

Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems.

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

IEEE Trans. Knowl. Data Eng., 2023

Learning to Generate Better Than Your LLM.

Jonathan D. Chang, Kianté Brantley, Rajkumar Ramamurthy, Dipendra Misra, Wen Sun

CoRR, 2023

Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization.

Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kianté Brantley, Jack Hessel, Rafet Sifa, Christian Bauckhage, Hannaneh Hajishirzi, Yejin Choi

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Bounding open space risk with decoupling autoencoders in open set recognition.

Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa

Int. J. Data Sci. Anal., 2022

Anonymization of German financial documents using neural network-based language models with contextual word representations.

David Biesner, Rajkumar Ramamurthy, Robin Stenzel, Max Lübbering, Lars Patrick Hillebrand, Anna Ladi, Maren Pielka, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa

Int. J. Data Sci. Anal., 2022

Zero-Shot Text Matching for Automated Auditing using Sentence Transformers.

David Biesner, Maren Pielka, Rajkumar Ramamurthy, Tim Dilmaghani Khameneh, Bernd Kliem, Rüdiger Loitz, Rafet Sifa

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

From Open Set Recognition Towards Robust Multi-class Classification.

Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

2021

Automatic Indexing of Financial Documents via Information Extraction.

Rajkumar Ramamurthy, Max Lübbering, Thiago Bell, Michael Gebauer, Bilge Ulusay, Daniel Uedelhoven, Tim Dilmaghani Khameneh, Rüdiger Loitz, Maren Pielka, Christian Bauckhage, Rafet Sifa

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Utilizing Representation Learning for Robust Text Classification Under Datasetshift.

Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Maren Pielka, Christian Bauckhage, Rafet Sifa

Proceedings of the LWDA 2021 Workshops: FGWM, 2021

Toxicity Detection in Online Comments with Limited Data: A Comparative Analysis.

Max Lübbering, Maren Pielka, Kajaree Das, Michael Gebauer, Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Decoupling Autoencoders for Robust One-vs-Rest Classification.

Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa

Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics, 2021

ALiBERT: improved automated list inspection (ALI) with BERT.

Rajkumar Ramamurthy, Maren Pielka, Robin Stenzel, Christian Bauckhage, Rafet Sifa, Tim Dilmaghani Khameneh, Ulrich Warning, Bernd Kliem, Rüdiger Loitz

Proceedings of the DocEng '21: ACM Symposium on Document Engineering 2021, 2021

2020

Matrix- and Tensor Factorization for Game Content Recommendation.

Rafet Sifa, Raheel Yawar, Rajkumar Ramamurthy, Christian Bauckhage, Kristian Kersting

Künstliche Intell., 2020

NLPGym - A toolkit for evaluating RL agents on Natural Language Processing Tasks.

Rajkumar Ramamurthy, Rafet Sifa, Christian Bauckhage

CoRR, 2020

Novelty-Guided Reinforcement Learning via Encoded Behaviors.

Rajkumar Ramamurthy, Rafet Sifa, Max Lübbering, Christian Bauckhage

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Tackling Contradiction Detection in German Using Machine Translation and End-to-End Recurrent Neural Networks.

Maren Pielka, Rafet Sifa, Lars Patrick Hillebrand, David Biesner, Rajkumar Ramamurthy, Anna Ladi, Christian Bauckhage

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Supervised Autoencoder Variants for End to End Anomaly Detection.

Max Lübbering, Michael Gebauer, Rajkumar Ramamurthy, Rafet Sifa, Christian Bauckhage

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

Guided Reinforcement Learning via Sequence Learning.

Rajkumar Ramamurthy, Rafet Sifa, Max Lübbering, Christian Bauckhage

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

From Imbalanced Classification to Supervised Outlier Detection Problems: Adversarially Trained Auto Encoders.

Max Lübbering, Rajkumar Ramamurthy, Michael Gebauer, Thiago Bell, Rafet Sifa, Christian Bauckhage

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Hopfield Networks for Vector Quantization.

Christian Bauckhage, Rajkumar Ramamurthy, Rafet Sifa

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

2019

Towards Contradiction Detection in German: a Translation-Driven Approach.

Rafet Sifa, Maren Pielka, Rajkumar Ramamurthy, Anna Ladi, Lars Patrick Hillebrand, Christian Bauckhage

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

A Community Detection Based Approach for Exploring Patterns in Player Reviews.

Maren Pielka, Rafet Sifa, Rajkumar Ramamurthy, César Ojeda, Christian Bauckhage

Proceedings of the Intelligent Systems and Applications, 2019

Echo State Networks for Named Entity Recognition.

Rajkumar Ramamurthy, Robin Stenzel, Rafet Sifa, Anna Ladi, Christian Bauckhage

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

Leveraging Domain Knowledge for Reinforcement Learning Using MMC Architectures.

Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa, Jannis Schücker, Stefan Wrobel

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

Towards Automated Auditing with Machine Learning.

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

Proceedings of the ACM Symposium on Document Engineering 2019, 2019

2018

Policy Learning Using SPSA.

Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa, Stefan Wrobel

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Matrix and Tensor Factorization Based Game Content Recommender Systems: A Bottom-Up Architecture and a Comparative Online Evaluation.

Rafet Sifa, Raheel Yawar, Rajkumar Ramamurthy, Christian Bauckhage

Proceedings of the Fourteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2018

2017

Using Echo State Networks for Cryptography.

Rajkumar Ramamurthy, Christian Bauckhage, Krisztián Búza, Stefan Wrobel

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017