| Latent dirichlet allocation DM Blei, AY Ng, MI Jordan the Journal of machine Learning research 3, 993-1022, 2003 | 40260 | 2003 |
| On spectral clustering: Analysis and an algorithm AY Ng, MI Jordan, Y Weiss Advances in neural information processing systems, 849-856, 2002 | 10089 | 2002 |
| ROS: an open-source Robot Operating System M Quigley, K Conley, B Gerkey, J Faust, T Foote, J Leibs, R Wheeler, ... ICRA workshop on open source software 3 (3.2), 5, 2009 | 8893 | 2009 |
| Recursive deep models for semantic compositionality over a sentiment treebank R Socher, A Perelygin, J Wu, J Chuang, CD Manning, AY Ng, C Potts Proceedings of the 2013 conference on empirical methods in natural language …, 2013 | 5590 | 2013 |
| Rectifier nonlinearities improve neural network acoustic models AL Maas, AY Hannun, AY Ng Proc. icml 30 (1), 3, 2013 | 5302 | 2013 |
| Distance metric learning with application to clustering with side-information E Xing, M Jordan, SJ Russell, A Ng Advances in neural information processing systems 15, 521-528, 2002 | 3596 | 2002 |
| Large scale distributed deep networks J Dean, G Corrado, R Monga, K Chen, M Devin, M Mao, M Ranzato, ... Advances in neural information processing systems 25, 1223-1231, 2012 | 3522 | 2012 |
| Efficient sparse coding algorithms H Lee, A Battle, R Raina, AY Ng Advances in neural information processing systems, 801-808, 2007 | 3217 | 2007 |
| Learning word vectors for sentiment analysis A Maas, RE Daly, PT Pham, D Huang, AY Ng, C Potts Proceedings of the 49th annual meeting of the association for computational …, 2011 | 3138 | 2011 |
| Reading digits in natural images with unsupervised feature learning Y Netzer, T Wang, A Coates, A Bissacco, B Wu, AY Ng | 3129 | 2011 |
| Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations H Lee, R Grosse, R Ranganath, AY Ng Proceedings of the 26th annual international conference on machine learning …, 2009 | 3013 | 2009 |
| On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes AY Ng, MI Jordan Advances in neural information processing systems, 841-848, 2002 | 2940 | 2002 |
| Apprenticeship learning via inverse reinforcement learning P Abbeel, AY Ng Proceedings of the twenty-first international conference on Machine learning, 1, 2004 | 2837 | 2004 |
| Multimodal deep learning J Ngiam, A Khosla, M Kim, J Nam, H Lee, AY Ng ICML, 2011 | 2818 | 2011 |
| An analysis of single-layer networks in unsupervised feature learning A Coates, A Ng, H Lee Proceedings of the fourteenth international conference on artificial …, 2011 | 2762 | 2011 |
| Building high-level features using large scale unsupervised learning QV Le 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 2615 | 2013 |
| Algorithms for inverse reinforcement learning. AY Ng, SJ Russell Icml 1, 2, 2000 | 2595 | 2000 |
| Deep speech 2: End-to-end speech recognition in english and mandarin D Amodei, S Ananthanarayanan, R Anubhai, J Bai, E Battenberg, C Case, ... International conference on machine learning, 173-182, 2016 | 2339 | 2016 |
| Cheap and fast–but is it good? evaluating non-expert annotations for natural language tasks R Snow, B O’connor, D Jurafsky, AY Ng Proceedings of the 2008 conference on empirical methods in natural language …, 2008 | 2321 | 2008 |
| Feature selection, L1 vs. L2 regularization, and rotational invariance AY Ng Proceedings of the twenty-first international conference on Machine learning, 78, 2004 | 2020 | 2004 |
