| Making deep neural networks robust to label noise: A loss correction approach G Patrini, A Rozza, A Krishna Menon, R Nock, L Qu Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1145 | 2017 |
| Autorec: Autoencoders meet collaborative filtering S Sedhain, AK Menon, S Sanner, L Xie Proceedings of the 24th international conference on World Wide Web, 111-112, 2015 | 1123 | 2015 |
| Link prediction via matrix factorization AK Menon, C Elkan Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011 | 652 | 2011 |
| Anomaly detection using one-class neural networks R Chalapathy, AK Menon, S Chawla arXiv preprint arXiv:1802.06360, 2018 | 419 | 2018 |
| The cost of fairness in binary classification AK Menon, RC Williamson Conference on Fairness, accountability and transparency, 107-118, 2018 | 323 | 2018 |
| Long-tail learning via logit adjustment AK Menon, S Jayasumana, AS Rawat, H Jain, A Veit, S Kumar arXiv preprint arXiv:2007.07314, 2020 | 279 | 2020 |
| Learning with symmetric label noise: The importance of being unhinged B Van Rooyen, A Menon, RC Williamson Advances in neural information processing systems 28, 2015 | 265 | 2015 |
| Learning from corrupted binary labels via class-probability estimation A Menon, B Van Rooyen, CS Ong, B Williamson International conference on machine learning, 125-134, 2015 | 222 | 2015 |
| Does label smoothing mitigate label noise? M Lukasik, S Bhojanapalli, A Menon, S Kumar International Conference on Machine Learning, 6448-6458, 2020 | 191 | 2020 |
| Response prediction using collaborative filtering with hierarchies and side-information AK Menon, KP Chitrapura, S Garg, D Agarwal, N Kota Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 185 | 2011 |
| A machine learning framework for programming by example A Menon, O Tamuz, S Gulwani, B Lampson, A Kalai International Conference on Machine Learning, 187-195, 2013 | 167 | 2013 |
| Robust, deep and inductive anomaly detection R Chalapathy, AK Menon, S Chawla Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 162 | 2017 |
| On the statistical consistency of algorithms for binary classification under class imbalance A Menon, H Narasimhan, S Agarwal, S Chawla International Conference on Machine Learning, 603-611, 2013 | 103 | 2013 |
| Fairness risk measures R Williamson, A Menon International Conference on Machine Learning, 6786-6797, 2019 | 94 | 2019 |
| Beam search algorithms for multilabel learning A Kumar, S Vembu, AK Menon, C Elkan Machine learning 92, 65-89, 2013 | 94 | 2013 |
| Can gradient clipping mitigate label noise? AK Menon, AS Rawat, SJ Reddi, S Kumar International Conference on Learning Representations, 2020 | 92 | 2020 |
| A log-linear model with latent features for dyadic prediction AK Menon, C Elkan 2010 IEEE international conference on data mining, 364-373, 2010 | 89 | 2010 |
| Fast algorithms for approximating the singular value decomposition AK Menon, C Elkan ACM Transactions on Knowledge Discovery from Data (TKDD) 5 (2), 1-36, 2011 | 82 | 2011 |
| Large-scale support vector machines: algorithms and theory AK Menon Research Exam, University of California, San Diego 117, 2009 | 82 | 2009 |
| Low-rank linear cold-start recommendation from social data S Sedhain, A Menon, S Sanner, L Xie, D Braziunas Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 76 | 2017 |
Sanjiv KumarGoogle Fellow, VP, Google ResearchVerified email at google.com
