| On large-batch training for deep learning: Generalization gap and sharp minima NS Keskar, D Mudigere, J Nocedal, M Smelyanskiy, PTP Tang arXiv preprint arXiv:1609.04836, 2016 | 964 | 2016 |
| Regularizing and optimizing LSTM language models S Merity, NS Keskar, R Socher arXiv preprint arXiv:1708.02182, 2017 | 519 | 2017 |
| Improving generalization performance by switching from adam to sgd NS Keskar, R Socher arXiv preprint arXiv:1712.07628, 2017 | 151 | 2017 |
| The natural language decathlon: Multitask learning as question answering B McCann, NS Keskar, C Xiong, R Socher arXiv preprint arXiv:1806.08730, 2018 | 150 | 2018 |
| An analysis of neural language modeling at multiple scales S Merity, NS Keskar, R Socher arXiv preprint arXiv:1803.08240, 2018 | 94 | 2018 |
| Ctrl: A conditional transformer language model for controllable generation NS Keskar, B McCann, LR Varshney, C Xiong, R Socher arXiv preprint arXiv:1909.05858, 2019 | 82 | 2019 |
| Weighted transformer network for machine translation K Ahmed, NS Keskar, R Socher arXiv preprint arXiv:1711.02132, 2017 | 57 | 2017 |
| Neural text summarization: A critical evaluation W Kryściński, NS Keskar, B McCann, C Xiong, R Socher arXiv preprint arXiv:1908.08960, 2019 | 35 | 2019 |
| Balancing communication and computation in distributed optimization AS Berahas, R Bollapragada, NS Keskar, E Wei IEEE Transactions on Automatic Control 64 (8), 3141-3155, 2018 | 29 | 2018 |
| A closer look at deep learning heuristics: Learning rate restarts, warmup and distillation A Gotmare, NS Keskar, C Xiong, R Socher arXiv preprint arXiv:1810.13243, 2018 | 26 | 2018 |
| Coarse-grain fine-grain coattention network for multi-evidence question answering V Zhong, C Xiong, NS Keskar, R Socher arXiv preprint arXiv:1901.00603, 2019 | 24 | 2019 |
| adaqn: An adaptive quasi-newton algorithm for training rnns NS Keskar, AS Berahas Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016 | 24 | 2016 |
| A second-order method for convex 1-regularized optimization with active-set prediction N Keskar, J Nocedal, F Öztoprak, A Waechter Optimization Methods and Software 31 (3), 605-621, 2016 | 21 | 2016 |
| Identifying generalization properties in neural networks H Wang, NS Keskar, C Xiong, R Socher arXiv preprint arXiv:1809.07402, 2018 | 17 | 2018 |
| A nonmonotone learning rate strategy for SGD training of deep neural networks NS Keskar, G Saon 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 10 | 2015 |
| A limited-memory quasi-Newton algorithm for bound-constrained non-smooth optimization N Keskar, A Wächter Optimization Methods and Software 34 (1), 150-171, 2019 | 9 | 2019 |
| Xlda: Cross-lingual data augmentation for natural language inference and question answering J Singh, B McCann, NS Keskar, C Xiong, R Socher arXiv preprint arXiv:1905.11471, 2019 | 8 | 2019 |
| On large-batch training for deep learning: Generalization gap and sharp minima. arXiv 2016 NS Keskar, D Mudigere, J Nocedal, M Smelyanskiy, PTP Tang arXiv preprint arXiv:1609.04836, 0 | 8 | |
| Using mode connectivity for loss landscape analysis A Gotmare, NS Keskar, C Xiong, R Socher arXiv preprint arXiv:1806.06977, 2018 | 6 | 2018 |
| Sequence-to-sequence prediction using a neural network model NS Keskar, K Ahmed, R Socher US Patent App. 15/884,125, 2019 | 5 | 2019 |
Richard SocherChief Scientist at SalesforceVerified email at stanford.edu
