Chandan K. Reddy
Affiliations: | Computer Science | Wayne State University, Detroit, MI, United States |
Area:
Computer Science, Bioinformatics BiologyGoogle:
"Chandan Reddy"Children
Sign in to add traineeNoor Alaydie | grad student | 2012 | Wayne State |
Omar Odibat | grad student | 2012 | Wayne State |
Samir Al-Stouhi | grad student | 2013 | Wayne State |
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Publications
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Dabiri S, Lu C, Heaslip K, et al. (2020) Semi-Supervised Deep Learning Approach for Transportation Mode Identification Using GPS Trajectory Data Ieee Transactions On Knowledge and Data Engineering. 32: 1010-1023 |
Dabiri S, Marković N, Heaslip K, et al. (2020) A deep convolutional neural network based approach for vehicle classification using large-scale GPS trajectory data Transportation Research Part C: Emerging Technologies. 116: 102644 |
Keneshloo Y, Shi T, Ramakrishnan N, et al. (2019) Deep Reinforcement Learning for Sequence-to-Sequence Models. Ieee Transactions On Neural Networks and Learning Systems |
Wang P, Li Y, Reddy CK. (2019) Machine Learning for Survival Analysis Acm Computing Surveys. 51: 1-36 |
Dave VS, Hasan MA, Zhang B, et al. (2018) Predicting interval time for reciprocal link creation using survival analysis Social Network Analysis and Mining. 8 |
Vinzamuri B, Li Y, Reddy CK. (2017) Pre-Processing Censored Survival Data Using Inverse Covariance Matrix Based Calibration Ieee Transactions On Knowledge and Data Engineering. 29: 2111-2124 |
Al-Stouhi S, Reddy CK. (2016) Transfer Learning for Class Imbalance Problems with Inadequate Data. Knowledge and Information Systems. 48: 201-228 |
Li Y, Bai C, Reddy CK. (2016) A Distributed Ensemble Approach for Mining Healthcare Data under Privacy Constraints. Information Sciences. 330: 245-259 |
Fard MJ, Wang P, Chawla S, et al. (2016) A Bayesian Perspective on Early Stage Event Prediction in Longitudinal Data Ieee Transactions On Knowledge and Data Engineering. 28: 3126-3139 |
Dutta JK, Banerjee B, Reddy CK. (2016) RODS: Rarity based Outlier Detection in a Sparse Coding Framework Ieee Transactions On Knowledge and Data Engineering. 28: 483-495 |