| Manifold regularization: A geometric framework for learning from labeled and unlabeled examples M Belkin, P Niyogi, V Sindhwani The Journal of Machine Learning Research 7, 2399-2434, 2006 | 5053 | 2006 |
| Recommender systems. P Melville, V Sindhwani Encyclopedia of machine learning 1, 829-838, 2010 | 917 | 2010 |
| Low-rank matrix factorization for deep neural network training with high-dimensional output targets TN Sainath, B Kingsbury, V Sindhwani, E Arisoy, B Ramabhadran 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 784 | 2013 |
| Beyond the point cloud: from transductive to semi-supervised learning V Sindhwani, P Niyogi, M Belkin Proceedings of the 22nd international conference on Machine learning, 824-831, 2005 | 611 | 2005 |
| Optimization techniques for semi-supervised support vector machines O Chapelle, V Sindhwani, SS Keerthi The Journal of Machine Learning Research 9, 203-233, 2008 | 586 | 2008 |
| A co-regularization approach to semi-supervised learning with multiple views V Sindhwani, P Niyogi, M Belkin Workshop on Learning with Multiple Views at ICML 2005, 2005 | 558 | 2005 |
| SystemML: Declarative machine learning on MapReduce A Ghoting, R Krishnamurthy, E Pednault, B Reinwald, V Sindhwani, ... Data Engineering (ICDE), 2011 IEEE 27th International Conference on, 231-242, 2011 | 460 | 2011 |
| Socratic models: Composing zero-shot multimodal reasoning with language A Zeng, M Attarian, B Ichter, K Choromanski, A Wong, S Welker, ... arXiv preprint arXiv:2204.00598, 2022 | 432 | 2022 |
| Transporter networks: Rearranging the visual world for robotic manipulation A Zeng, P Florence, J Tompson, S Welker, J Chien, M Attarian, ... Conference on Robot Learning, 726-747, 2021 | 430 | 2021 |
| Data quality from crowdsourcing: a study of annotation selection criteria PY Hsueh, P Melville, V Sindhwani Proceedings of the NAACL HLT 2009 workshop on active learning for natural …, 2009 | 409 | 2009 |
| On manifold regularization M Belkin, P Niyogi, V Sindhwani International Workshop on Artificial Intelligence and Statistics, 17-24, 2005 | 343 | 2005 |
| Large scale semi-supervised linear SVMs V Sindhwani, SS Keerthi Proceedings of the 29th annual international ACM SIGIR conference on …, 2006 | 323 | 2006 |
| An RKHS for multi-view learning and manifold co-regularization V Sindhwani, DS Rosenberg Proceedings of the 25th international conference on Machine learning, 976-983, 2008 | 297 | 2008 |
| Structured transforms for small-footprint deep learning V Sindhwani, T Sainath, S Kumar Advances in Neural Information Processing Systems 28, 2015 | 285 | 2015 |
| Document-word co-regularization for semi-supervised sentiment analysis V Sindhwani, P Melville Data Mining, 2008. ICDM'08. Eighth IEEE International Conference on, 1025-1030, 2008 | 285 | 2008 |
| A non-negative matrix tri-factorization approach to sentiment classification with lexical prior knowledge T Li, Y Zhang, V Sindhwani Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL …, 2009 | 236 | 2009 |
| An efficient method for gradient-based adaptation of hyperparameters in SVM models S Keerthi, V Sindhwani, O Chapelle | 208 | 2007 |
| Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization A Saha, V Sindhwani Proceedings of the fifth ACM international conference on Web search and data …, 2012 | 202 | 2012 |
| Branch and bound for semi-supervised support vector machines O Chapelle, V Sindhwani, S Keerthi | 190 | 2007 |
| Learning to rearrange deformable cables, fabrics, and bags with goal-conditioned transporter networks D Seita, P Florence, J Tompson, E Coumans, V Sindhwani, K Goldberg, ... 2021 IEEE International Conference on Robotics and Automation (ICRA), 4568-4575, 2021 | 186 | 2021 |
Krzysztof ChoromanskiGoogle DeepMind Robotics & Columbia UniversityVerified email at columbia.edu
