# Publications

### Journal Articles

- M. Yu, K. N. Ramamurthy, A. Thompson, and A. C. Lozano, “Simultaneous Parameter Learning and Bi-Clustering for Multi-Response Models,”
*Frontiers in Big Data*, vol. 2, 2019. - M. Arnold
*et al.*, “FactSheets: Increasing trust in AI services through supplier’s declarations of conformity,”*IBM Journal of Research and Development*, vol. 63, no. 4/5, pp. 6:1-6:13, 1 July-Sept. 2019. - R. K. E. Bellamy
*et al.*, “AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias,”*IBM Journal of Research and Development*, vol. 63, no. 4/5, pp. 4:1-4:15, 1 July-Sept. 2019. - R. K. E. Bellamy
*et al.*, “Think Your Artificial Intelligence Software Is Fair? Think Again,” in*IEEE Software,*vol. 36, no. 4, pp. 76-80, July-Aug. 2019. doi: 10.1109/MS.2019.2908514 - D. Wei, K. N. Ramamurthy, and K. R. Varshney, “Distribution preserving k-anonymity,”
*Statistical Analysis and Data Mining: The ASA Data Science Journal*, 2018. - F. Calmon, D. Wei, B. Vinzamuri, K. N. Ramamurthy, K. R. Varshney, “Data Pre-Processing for Discrimination Prevention: Information-Theoretic Optimization and Analysis,”
*IEEE Journal of Selected Topics in Signal Processing*, 12(5), 1106-1119, 2018. - C. Kuhlman, K. N. Ramamurthy, P. Sattigeri, A. C. Lozano, L. Cao, C. Reddy, A. Mojsilovic, and K. R. Varshney , “How to Foster Innovation: A Data-Driven Approach to Measuring Economic Competitiveness,”
*IBM Journal of Research and Development*, 2017. - K. R. Varshney, D. Wei, K. N. Ramamurthy, and A. Mojsilovi'{c}, “Data Challenges in Disease Response: The 2014 Ebola Outbreak and Beyond”,
*ACM Journal of Data and Information Quality*, 2015. - K. N. Ramamurthy, L. A. Hinnov, and A. Spanias, “Teaching Earth Signals Analysis using the Java-DSP Earth Systems Edition: Modern and Past Climate Change,”
*Journal of Geoscience Education*, 2014. - J. J. Thiagarajan, K. N. Ramamurthy, and A. Spanias, “Learning Stable Multilevel Dictionaries for Sparse Representations,”
*IEEE Transactions on Neural Networks and Learning Systems*, 2014. - J. J. Thiagarajan, K. N. Ramamurthy, and A. Spanias, “Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning,”
*IEEE Transactions on Image Processing*, 2014. - J. J. Thiagarajan, K. N. Ramamurthy, D. Rajan, A. Puri, D. Frakes, and A. Spanias, “Kernel sparse models for automated tumor segmentation,”
*International Journal on Artificial Intelligence Tools*, 2014 (**invited paper**). - K. N. Ramamurthy, J. J. Thiagarajan, and A. Spanias, “Recovering Non-negative and Combined Sparse Representations,”
*Digital Signal Processing*, 2013. - J. J. Thiagarajan, K. N. Ramamurthy, and A. Spanias, “Mixing matrix estimation using discriminative clustering for blind source separation,”
*Digital Signal Processing*, 2012. - J. J. Thiagarajan, K. N. Ramamurthy, and A. Spanias, “Optimality and Stability of the K-hyperline Clustering Algorithm,”
*Pattern Recognition Letters*, 2011. - K. N. Ramamurthy, J. J. Thiagarajan, P. Sattigeri, and A. Spanias, “Transform Domain Features for Ion-channel Signal Classification”,
*Biomedical Signal Processing and Control*, 2010.

### Conference Proceedings (from 2018 - see CV for the full list)

- D. Wei, K. N. Ramamurthy, and F. Calmon “Optimized Score Transformation for Fair Classification,”
*AISTATS*, 2020 (to appear). paper code - P. Zhao, P.-Y. Chen, Payel Das, K. N. Ramamurthy, and X. Lin, “Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness,”
*ICLR*, 2020. - M. Oh, P. Olsen, and K. N. Ramamurthy, “Crowd Counting with Decomposed Uncertainty,”
*AAAI*, 2020. - S. Subramanian, I. Baldini, S. Ravichandran, D. A. Katz-Rogozhnikov, K. N. Ramamurthy, P. Sattigeri, K. R. Varshney, A. Wang, P. Mangalath, and L. B. Kleiman, “A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications,”
*IAAI*, 2020. - M. Singh, and K. N. Ramamurthy, “Understanding racial bias in health using the Medical Expenditure Panel Survey data,”
*NeurIPS Workshop on Fair ML for Health*, 2019 (**Spotlight presentation**). - S. Subramanian
*et al.*, “Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies,”*NeurIPS 2019 Workshop on Machine Learning for Health*, 2019. - N. Codella, M. Hind, K. N. Ramamurthy, M. Campbell, A. Dhurandhar, K. Varshney, D. Wei, and A. Mojsilovic, “Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning”,
*ICML Workshop on Human In the Loop Learning*, 2019. - K. N. Ramamurthy, K. R. Varshney, and K. Mody, “Topological Data Analysis of Decision Boundaries with Application to Model Selection,”
*ICML*, 2019. - P. K. Lohia, K. N. Ramamurthy, M. Bhide, D. Saha, K. R. Varshney, and R. Puri, “Bias Mitigation Post-processing for Individual and Group Fairness,”
*IEEE ICASSP*, 2019. - A. Coston, K. N. Ramamurthy, D. Wei, K. Varshney, S. Speakman, Z. Mustahsan, and S. Chakraborty, “Fair Transfer Learning with Missing Protected Attributes,”
*AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society,*Jan. 2019. - N. Codella, M. Hind, K. N. Ramamurthy, M. Campbell, A. Dhurandhar, K. Varshney, D. Wei, and A. Mojsilovic, “TED: Teaching AI to Explain its Decisions,”
*AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society*, Jan. 2019. - P. Sattigeri, S. Ghosh, A. Kumar, K. N. Ramamurthy, S. Hoffman, Y. Drissi, and I. Padhi, “Probabilistic Mixture of Model-Agnostic Meta-Learners,”
*Proc. NeurIPS Workshop on Bayesian Deep Learning*, Dec. 2018. - P. Olsen, K. N. Ramamurthy, J. Ribera, Y. Chen, A. Thompson, R. Luss, M. Tuinstra, and N. Abe, “Detecting and Counting Panicles in Sorghum Images,”
*Proc. IEEE DSAA*, Oct. 2018. - P. Olsen, K. N. Ramamurthy, J. Ribera, Y. Chen, A. Thompson, R. Luss, M. Tuinstra, and N. Abe, “Learning to Detect and Count Panicles in Sorghum Images,”
*Proc. KDD FEED Workshop*, Aug. 2018. - A. Som, K. Thopalli, K. N. Ramamurthy, V. Venkataraman, A. Shukla, and P. Turaga, “Perturbation Robust Representations of Topological Persistence Diagrams,”
*Proc. of European Conference on Computer Vision*, Sep. 2018. - W. Zhang, R. Horesh, K. N. Ramamurthy, L. Wu, J. Yi, K. Anderson, and K. R. Varshney, “Financial Forecasting and Analysis for Low-Wage Workers,”
*Bloomberg Data for Good Exchange*, Sep. 2018. - J. J. Thiagarajan, S. Liu, K. N. Ramamurthy, and P-T. Bremer. “Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections,” In
*Computer Graphics Forum*, 37(3), pp. 241-251, Jul. 2018.

### Book Chapters

- A. Som, K. N. Ramamurthy, and P. Turaga, “Geometric Metrics for Topological Representations.” In
*Handbook of Variational Methods for Nonlinear Geometric Data*, Springer, 2020. - C.-C. Lin, K. N. Ramamurthy, and S. U. Pankanti, “Moving Camera Analytics: Computer Vision Applications.” In
*Embedded, Cyber-Physical, and IoT Systems*, pp. 89-113. Springer, Cham, 2020.

### Books

- J. J. Thiagarajan, K. N. Ramamurthy, and A. Spanias, “Sparse Representations for Image Understanding,”
*Synthesis Lectures on Image, Video and Multimedia*, Morgan and Claypool Publishers, 2014. - K. N. Ramamurthy and A. Spanias, “MATLAB Software for the Code Excited Linear Prediction Algorithm,”
*Synthesis Lectures on Algorithms and Software in Engineering*, Morgan and Claypool Publishers, 2010.