| 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 | 602 | 2015 |
| Link prediction via matrix factorization AK Menon, C Elkan Joint european conference on machine learning and knowledge discovery in …, 2011 | 544 | 2011 |
| 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 | 417 | 2017 |
| Large-scale support vector machines: algorithms and theory AK Menon Research Exam, University of California, San Diego 117, 2009 | 188 | 2009 |
| 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 | 158 | 2011 |
| Anomaly detection using one-class neural networks R Chalapathy, AK Menon, S Chawla arXiv preprint arXiv:1802.06360, 2018 | 157 | 2018 |
| 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 | 144 | 2015 |
| Learning with symmetric label noise: The importance of being unhinged B Van Rooyen, AK Menon, RC Williamson arXiv preprint arXiv:1505.07634, 2015 | 135 | 2015 |
| The cost of fairness in binary classification AK Menon, RC Williamson Conference on Fairness, Accountability and Transparency, 107-118, 2018 | 126 | 2018 |
| 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 | 120 | 2013 |
| A log-linear model with latent features for dyadic prediction AK Menon, C Elkan 2010 IEEE International Conference on Data Mining, 364-373, 2010 | 83 | 2010 |
| Robust, deep and inductive anomaly detection R Chalapathy, AK Menon, S Chawla Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017 | 82 | 2017 |
| Beam search algorithms for multilabel learning A Kumar, S Vembu, AK Menon, C Elkan Machine learning 92 (1), 65-89, 2013 | 74 | 2013 |
| 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 | 69 | 2011 |
| 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 | 64 | 2013 |
| Predicting labels for dyadic data AK Menon, C Elkan Data Mining and Knowledge Discovery 21 (2), 327-343, 2010 | 58 | 2010 |
| Learning and inference in probabilistic classifier chains with beam search A Kumar, S Vembu, AK Menon, C Elkan Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012 | 47 | 2012 |
| A colorful approach to text processing by example K Yessenov, S Tulsiani, A Menon, RC Miller, S Gulwani, B Lampson, ... Proceedings of the 26th annual ACM symposium on User interface software and …, 2013 | 46 | 2013 |
| 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 | 41 | 2017 |
| Detecting inappropriate access to electronic health records using collaborative filtering AK Menon, X Jiang, J Kim, J Vaidya, L Ohno-Machado Machine learning 95 (1), 87-101, 2014 | 41 | 2014 |
Charles ElkanProfessor of Computer Science, University of California, San DiegoVerified email at ucsd.edu
