| A structured self-attentive sentence embedding Z Lin, M Feng, CN Santos, M Yu, B Xiang, B Zhou, Y Bengio arXiv preprint arXiv:1703.03130, 2017 | 2906 | 2017 |
| Applying deep learning to answer selection: A study and an open task M Feng, B Xiang, MR Glass, L Wang, B Zhou 2015 IEEE workshop on automatic speech recognition and understanding (ASRU …, 2015 | 459 | 2015 |
| A structured self-attentive sentence embedding. arXiv 2017 Z Lin, M Feng, CN Santos, M Yu, B Xiang, B Zhou, Y Bengio arXiv preprint arXiv:1703.03130, 2017 | 68 | 2017 |
| Forecast of solar energy production-A deep learning approach R Zhang, M Feng, W Zhang, S Lu, F Wang 2018 IEEE International Conference on Big Knowledge (ICBK), 73-82, 2018 | 63 | 2018 |
| Efficient Hyper-parameter Optimization for NLP Applications L Wang, M Feng, B Zhou, B Xiang, S Mahadevan EMNLP2015, 2015 | 53 | 2015 |
| Local multicast in single-host multi-GPU machine for distributed deep learning systems M Feng, Y Ren, Y Wang, L Zhang, W Zhang US Patent 10,614,356, 2020 | 23 | 2020 |
| A structured self-attentive sentence embedding (2017) Z Lin, M Feng, CN Dos Santos, M Yu, B Xiang, B Zhou, Y Bengio arXiv preprint arXiv:1703.03130, 2017 | 23 | 2017 |
| Advancements in Reordering Models for Statistical Machine Translation M Feng, JT Peter, H Ney ACL 2013, 2013 | 22 | 2013 |
| A source-side decoding sequence model for statistical machine translation M Feng, A Mauser, H Ney Proceedings of the 9th Conference of the Association for Machine Translation …, 2010 | 21 | 2010 |
| An efficient, distributed stochastic gradient descent algorithm for deep-learning applications G Cong, O Bhardwaj, M Feng 2017 46th International Conference on Parallel Processing (ICPP), 11-20, 2017 | 18 | 2017 |
| The RWTH Aachen Machine Translation Systems for IWSLT 2013 J Wuebker, S Peitz, T Alkhouli, JT Peter, M Feng, M Freitag, H Ney IWSLT 2013, 2013 | 18 | 2013 |
| The RWTH Aachen Machine Translation System for IWSLT 2011 J Wuebker, M Huck, S Mansour, M Freitag, M Feng, S Peitz, C Schmidt, ... International Workshop on Spoken Language Translation, 106-113, 2011 | 18 | 2011 |
| Gadei: On scale-up training as a service for deep learning W Zhang, M Feng, Y Zheng, Y Ren, Y Wang, J Liu, P Liu, B Xiang, ... 2017 IEEE International Conference on Data Mining (ICDM), 1195-1200, 2017 | 14 | 2017 |
| Semantic cohesion model for phrase-based SMT M Feng, W Sun, H Ney Proceedings of COLING 2012, 867-878, 2012 | 14 | 2012 |
| Fourier transformer: Fast long range modeling by removing sequence redundancy with fft operator Z He, M Yang, M Feng, J Yin, X Wang, J Leng, Z Lin arXiv preprint arXiv:2305.15099, 2023 | 13 | 2023 |
| Storage controller acceleration for neural network training and inference M Feng, Y Ren, Y Wang, L Zhang, W Zhang US Patent 11,138,494, 2021 | 13 | 2021 |
| Hybrid aggregation for deep learning neural networks M Feng, Y Ren, Y Wang, L Zhang, W Zhang US Patent 10,783,437, 2020 | 13 | 2020 |
| Local system voting feature for machine translation system combination M Freitag, JT Peter, S Peitz, M Feng, H Ney arXiv preprint arXiv:1702.03033, 2017 | 12 | 2017 |
| The RWTH Aachen System for NTCIR-9 PatentMT M Feng, C Schmidt, J Wuebker, S Peitz, M Freitag, H Ney Proceedings of the NTCIR-9 Workshop, Tokyo, Japan, 2011 | 12 | 2011 |
| Distributed deep learning for question answering M Feng, B Xiang, B Zhou Proceedings of the 25th ACM International on Conference on Information and …, 2016 | 11 | 2016 |
Hermann NeyRWTH Aachen UniversityEmail được xác minh tại cs.rwth-aachen.de
