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Jinseok Nam
Jinseok Nam
Amazon Alexa AI
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Titel
Zitiert von
Zitiert von
Jahr
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
4782014
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
2012017
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
732016
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
592016
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
472012
Medical Concept Embeddings via Labeled Background Corpora
EL Mencıa, G de Melo, J Nam
International Conference on Language Resources and Evaluation (LREC), 2016
262016
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
232016
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
222019
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
172015
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
92021
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
82016
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
62013
Learning label structures with neural networks for multi-label classification
J Nam
Dissertation, Darmstadt, Technische Universität Darmstadt, 2018, 2019
42019
Semi-Supervised Neural Networks for Nested Named Entity Recognition
J Nam
Workshop proceedings of the 12th edition of the KONVENS conference, 144-148, 2014
42014
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
22023
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
22022
Knowledge discovery in scientific literature
J Nam, C Kirschner, Z Ma, N Erbs, S Neumann, D Oelke, S Remus, ...
Universitätsbibliothek Hildesheim, 2014
12014
On Learning Vector Representations in Hierarchical Label Spaces
J Nam, J Fürnkranz
arXiv preprint arXiv:1412.6881, 2014
2014
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