Michael Glueck, Mahdi Pakdaman Naeini, Finale Doshi-Velez, Fanny Chevalier, Azam Khan, Daniel Wigdor, and Michael Brudno. 2018. “PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models.” IEEE Transactions on Visualization and Computer Graphics.

Mahdi Pakdaman Naeini and Gregory F Cooper. 2017. “Binary classifier calibration using an ensemble of piecewise linear regression models.” Knowledge and Information Systems, Pp. 1–20.

Fattaneh Jabbari, Mahdi Pakdaman Naeini, and Gregory Cooper. 2017. “Obtaining Accurate Probabilistic Causal Inference by Post-Processing Calibration.” In NIPS 2017 Workshop on Causal Inference and Machine Learning. whatif_paper.pdf

Mahdi Pakdaman Naeini, Fattaneh Jabbari, and Gregory Cooper. 2017. “An Assessment of the Calibration of Causal Relationships Learned Using RFCI and Bootstrapping.” In 4th Workshop on Data Mining for Medical Informatics: Causal Inference for Health Data Analytics. dmmi_paper.pdf

Mahdi Pakdaman Naeini and Gregory F Cooper. 2016. “Binary Classifier Calibration Using an Ensemble of Linear Trend Estimation.” In Proceedings of the 2016 SIAM International Conference on Data Mining, Pp. 261–269. SIAM.

Mahdi Pakdaman Naeini and Gregory F Cooper. 2016. “Binary Classifier Calibration using an Ensemble of Near Isotonic Regression Models.” In Data Mining (ICDM), 2016 IEEE 16th International Conference on, Pp. 360–369. IEEE.

Mahdi Pakdaman Naeini, Gregory F Cooper, and Milos Hauskrecht. 2015. “Binary classifier calibration using a Bayesian non-parametric approach.” In Proceedings of the 2015 SIAM International Conference on Data Mining, Pp. 208–216. SIAM.

Mahdi Pakdaman Naeini, Gregory F Cooper, and Milos Hauskrecht. 2015. “Obtaining Well Calibrated Probabilities Using Bayesian Binning.” In AAAI, Pp. 2901–2907.

Mahdi Pakdaman Naeini, Gregory F Cooper, and Milos Hauskrecht. 2014. “Binary Classifier Calibration: Non-parametric approach.” arXiv preprint arXiv:1401.3390.

Mahdi Pakdaman Naeini, Behzad Moshiri, Babak Nadjar Araabi, and Mehdi Sadeghi. 2014. “Learning by abstraction: Hierarchical classification model using evidential theoretic approach and Bayesian ensemble model.” Neurocomputing, 130, Pp. 73–82.

Mahdi Pakdaman Naeini, Iyad Batal, Zitao Liu, Charmgil Hong, and Milos Hauskrecht. 2014. “An Optimization-based Framework to Learn Conditional Random Fields for Multi-label Classification.” In Proceedings of the 2014 SIAM International Conference on Data Mining, Pp. 992–1000. SIAM.

Avneesh Saluja, Mahdi Pakdaman, Dongzhen Piao, and Ankur P Parikh. 2013. “Infinite Mixed Membership Matrix Factorization.” In IEEE 13th International Conference on Data Mining Workshops (ICDMW), Pp. 800–807. IEEE.

Hamidreza Taremian and Mahdi Pakdaman Naeini. 2011. “Hybrid Intelligent Decision Support System for credit risk assessment.” In 7th International Conference on Information Assurance and Security (IAS), Pp. 167–172. IEEE.

Homa Baradaran Hashemi, Nasser Yazdani, Azadeh Shakery, and Mahdi Pakdaman Naeini. 2010. “Application of ensemble models in web ranking.” In 5th International Symposium on Telecommunications (IST), Pp. 726–731. IEEE.

Mahdi Pakdaman Naeini, Hamidreza Taremian, and Homa Baradaran Hashemi. 2010. “Stock market value prediction using neural networks.” In International Conference on Computer Information Systems and Industrial Management Applications (CISIM), Pp. 132–136. IEEE.

Homa Baradaran Hashemi, Azadeh Shakery, and Mahdi Pakdaman Naeini. 2009. “Protein fold pattern recognition using Bayesian ensemble of RBF neural networks.” In International Conference of Soft Computing and Pattern Recognition (SOCPAR'09), Pp. 436–441. IEEE.