| Large-scale multi-label text classification—revisiting neural networks J Nam, J Kim, E Loza Mencía, I Gurevych, J Fürnkranz Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014 | 499 | 2014 |
| Maximizing subset accuracy with recurrent neural networks in multi-label classification J Nam, E Loza Mencía, HJ Kim, J Fürnkranz Advances in neural information processing systems 30, 2017 | 226 | 2017 |
| All-in text: Learning Document, Label, and Word Representations Jointly J Nam, E Loza Mencía, J Fürnkranz Thirtieth AAAI Conference on Artificial Intelligence, 1948--1954, 2016 | 75 | 2016 |
| Using Semantic Similarity for Multi-Label Zero-Shot Classification of Text Documents SP Veeranna, J Nam, EL Mencıa, J Fürnkranz European Symposium on Artificial Neural Networks (ESANN), 2016 | 64 | 2016 |
| Learning semantics with deep belief network for cross-language information retrieval J Kim, J Nam, I Gurevych Proceedings of COLING 2012: Posters, 579-588, 2012 | 47 | 2012 |
| Medical Concept Embeddings via Labeled Background Corpora EL Mencıa, G de Melo, J Nam International Conference on Language Resources and Evaluation (LREC), 2016 | 26 | 2016 |
| Improve sentiment analysis of citations with author modelling Z Ma, J Nam, K Weihe Proceedings of the 7th workshop on computational approaches to subjectivity …, 2016 | 23 | 2016 |
| Learning context-dependent label permutations for multi-label classification J Nam, YB Kim, EL Mencia, S Park, R Sarikaya, J Fürnkranz International Conference on Machine Learning, 4733-4742, 2019 | 22 | 2019 |
| Predicting unseen labels using label hierarchies in large-scale multi-label learning J Nam, E Loza Mencía, HJ Kim, J Fürnkranz Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015 | 17 | 2015 |
| Weakly supervised referring image segmentation with intra-chunk and inter-chunk consistency J Lee, S Lee, J Nam, S Yu, J Do, T Taghavi Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 13 | 2023 |
| What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation F Hirschmann, J Nam, J Fürnkranz International Conference on Computational Linguistics (COLING), 2016 | 11 | 2016 |
| Neural model robustness for skill routing in large-scale conversational ai systems: A design choice exploration H Li, S Park, A Dara, J Nam, S Lee, YB Kim, S Matsoukas, R Sarikaya arXiv preprint arXiv:2103.03373, 2021 | 9 | 2021 |
| Learning multi-labeled bioacoustic samples with an unsupervised feature learning approach EL Mencıa, J Nam, DH Lee Proc of Neural Information Processing Scaled for Bioacoustics, joint to NIPS …, 2013 | 6 | 2013 |
| Learning label structures with neural networks for multi-label classification J Nam Dissertation, Darmstadt, Technische Universität Darmstadt, 2018, 2019 | 4 | 2019 |
| Semi-Supervised Neural Networks for Nested Named Entity Recognition J Nam Workshop proceedings of the 12th edition of the KONVENS conference, 144-148, 2014 | 4 | 2014 |
| Scalable and robust self-learning for skill routing in large-scale conversational AI systems M Kachuee, J Nam, S Ahuja, JM Won, S Lee North American Chapter of the Association for Computational Linguistics …, 2022 | 3 | 2022 |
| Knowledge discovery in scientific literature J Nam, C Kirschner, Z Ma, N Erbs, S Neumann, D Oelke, S Remus, ... Universitätsbibliothek Hildesheim, 2014 | 1 | 2014 |
| On Learning Vector Representations in Hierarchical Label Spaces J Nam, J Fürnkranz arXiv preprint arXiv:1412.6881, 2014 | | 2014 |
