| Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks F Ma, R Chitta, J Zhou, Q You, T Sun, J Gao ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2017 | 369 | 2017 |
| Approximate kernel k-means: Solution to large scale kernel clustering R Chitta, R Jin, TC Havens, AK Jain Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 211 | 2011 |
| Kame: Knowledge-based attention model for diagnosis prediction in healthcare F Ma, Q You, H Xiao, R Chitta, J Zhou, J Gao Proceedings of the 27th ACM International Conference on Information and …, 2018 | 160 | 2018 |
| Quanzeng You, Tong Sun, and Jing Gao. 2017. Dipole: Diagnosis prediction in healthcare via attention-based bidirectional recurrent neural networks F Ma, R Chitta, J Zhou Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 1903 | 147 | 1903 |
| Efficient kernel clustering using random fourier features R Chitta, R Jin, AK Jain 2012 IEEE 12th International Conference on Data Mining, 161-170, 2012 | 115 | 2012 |
| Deep Multimodal Representation Learning From Temporal Data X Yang, P Ramesh, R Chitta, S Madhvanath, EA Bernal, J Luo IEEE Conference on Computer Vision and Pattern Recognition, 2017 | 111 | 2017 |
| Speedup of fuzzy and possibilistic kernel c-means for large-scale clustering TC Havens, R Chitta, AK Jain, R Jin 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), 463-470, 2011 | 39 | 2011 |
| Two-level k-means clustering algorithm for k–τ relationship establishment and linear-time classification R Chitta, MN Murty Pattern Recognition 43 (3), 796-804, 2010 | 37 | 2010 |
| A general framework for diagnosis prediction via incorporating medical code descriptions F Ma, Y Wang, H Xiao, Y Yuan, R Chitta, J Zhou, J Gao 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018 | 30 | 2018 |
| Scalable kernel clustering: Approximate kernel k-means R Chitta, R Jin, TC Havens, AK Jain arXiv preprint arXiv:1402.3849, 2014 | 23 | 2014 |
| Kernel-based clustering of big data R Chitta Michigan State University, 2015 | 13 | 2015 |
| Semi-supervised clustering A Jain, R Jin, R Chitta Handbook of Cluster Analysis, 1-35, 2014 | 13 | 2014 |
| Long-term memory networks for question answering F Ma, R Chitta, S Kataria, J Zhou, P Ramesh, T Sun, J Gao arXiv preprint arXiv:1707.01961, 2017 | 12 | 2017 |
| Sparse Kernel Clustering of Massive High-Dimensional Data sets with Large Number of Clusters R Chitta, AK Jain, R Jin PhD Workshop at CIKM, 2015 | 12 | 2015 |
| Stream Clustering: Efficient Kernel-based Approximation using Importance Sampling R Chitta, R Jin, AK Jain ICDM Workshop on Data Science and Big Data Analytics, 2015 | 9 | 2015 |
| Incorporating medical code descriptions for diagnosis prediction in healthcare F Ma, Y Wang, H Xiao, Y Yuan, R Chitta, J Zhou, J Gao BMC medical informatics and decision making 19 (6), 1-13, 2019 | 5 | 2019 |
| A Reliable and Accurate Multiple Choice Question Answering System for Due Diligence R Chitta, AK Hudek International Conference on Artificial Intelligence and Law, 2019 | 4 | 2019 |
| Clustering big data A Jain, R Chitta, R Jin Unpublished lecture notes, Department of Computer Science, Michigan State …, 2012 | 4 | 2012 |
| Long-term memory networks for knowledge extraction from text and publications F Ma, R Chitta, J Zhou, PS Ramesh, T Sun, SS Kataria US Patent 10,963,789, 2021 | 1 | 2021 |
| System and method for applying artificial intelligence techniques to respond to multiple choice questions R Chitta, AK Hudek US Patent App. 16/182,541, 2020 | 1 | 2020 |
Fenglong MaAssistant Professor at Pennsylvania State UniversityVerified email at psu.edu
