Publications

2018
Dhami, D.S., Kunapuli, G., Das, M., Page, D., & Natarajan, S., Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities, IEEE Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) 2018.
Natarajan, S., Das, S., Ramaman, N., Kunapuli, G., & Radivojac, P., Whom Should I Perform the Lab Test on Next? An Active Feature Elicitation Approach, International Joint Conference on Artificial Intelligence (IJCAI) 2018.
Odom, P., & Natarajan, S., Human-Guided Learning for Probabilistic Logic Models, Frontiers in Robotics and AI (Front. Robot. AI) 2018.
Das, M., Odom, P., Islam, M.R., Doppa, J., Roth, D., & Natarajan, S., Preference- Guided Planning: An Active Elicitation Approach, International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2018.
Molina, A., Vergari, A., Mauro, N.D., Esposito, F., Natarajan, S., & Kersting, K., Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains, In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2018.

2017
Yang, S., Hadiji, F., Kersting, K., Grannis, S., & Natarajan, S., Modeling Heart Procedures from EHRs: An Application of Exponential Families, IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM) 2017.
Ramanan, N., Yang, S., Grannis, S., & Natarajan, S., Discriminative Boosted Bayes Networks for Learning Multiple Cardiovascular Procedures, IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM) 2017.
Hayes, A.L., Das, M., Odom, P., & Natarajan, S., User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams, Knowledge Capture Conference 2017.
Natarajan, S., Prabhakar, A., Ramanan, N., Bagilone, A., Siek, K., & Connelly, K., Boosting for Post Partum Depression Prediction, IEEE Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) 2017.
Kaur, N., Kunapuli, G., Khot, T., Kersting, K., Cohen, W., & Natarajan, S., Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach, International Conference on Inductive Logic Programming (ILP) 2017.
Yang, S., Korayem, M., Aljadda, K., Grainger, T., & Natarajan, S., Combining content-based and collaborative filtering for job recommendation system: A cost-sensitive Statistical Relational Learning approach, Knowledge-Based Systems 2017.
Dhami, D.S., Soni, A., Page, D., & Natarajan, S., Identifying Parkinson's Patients : A Functional Gradient Boosting Approach, Artificial Intelligence in Medicine (AIME) 2017.
Molina, A., Natarajan, S., & Kersting, K., Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions, Thirty First AAAI Conference on Artificial Intelligence (AAAI) 2017.
Dhami, D.S., Leake, D., & Natarajan, S., Knowledge-based Morphological Classification of Galaxies from Vision Features, Knowledge-Based Techniques for Problem Solving and Reasoning (AAAI) 2017.
Das, M., Islam, M.R., Doppa, J.R., Roth, D., & Natarajan, S., Active Preference Elicitation for Planning, Human-Machine Collaborative Learning (AAAI) 2017.

2016
Malec, M., Khot, T., Nagy, J., Blasch, E., & Natarajan, S., Inductive Logic Programming meets Relational Databases: An Application to Statistical Relational Learning, International Conference on Inductive Logic Programming (ILP) 2016.
Soni, A., Viswanathan, D., Shavlik, J., & Natarajan, S., Learning Relational Dependency Networks for Relation Extraction, International Conference on Inductive Logic Programming (ILP) 2016.
Odom, P., Kumaraswamy, R., Kersting, K., & Natarajan, S., Learning through Advice-Seeking via Transfer, International Conference on Inductive Logic Programming (ILP) 2016.
Odom, P., & Natarajan, S., Actively Interacting with Experts: A Probabilistic Logic Approach, European Conference on Machine Learning and Principles of Knowledge Discovery in Databases (ECMLPKDD) 2016.
MacLeod, H., Yang, S., Oakes, K., Connelly, K., & Natarajan, S., Identifying Rare Diseases from Behavioural Data: A Machine Learning Approach, IEEE Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) 2016.
Odom, P., & Natarajan, S., Active Advice Seeking for Inverse Reinforcement Learning, International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2016.
Das, M., Wu, Y., Khot, T., Kersting, K., & Natarajan, S., Scaling Lifted Probabilistic Inference and Learning Via Graph Databases, SIAM International Conference on Data Mining (SDM) 2016.
Yang, S., Khot, T., Kersting, K., & Natarajan, S., Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach, Thirtieth AAAI Conference on Artificial Intelligence (AAAI) 2016.

2015
Kumaraswamy, R., Odom, P., Kersting, K., Leake, D., & Natarajan, S., Transfer Learning via Relational Type Matching, International Conference on Data Mining (ICDM) 2015.
Das, M., Wu, Y., Khot, T., Kersting, K., & Natarajan, S., Graph-based Approximate Counting for Relational Probabilistic Models, International Workshop on Statistical Relational AI (StarAI) 2015.
Kumaraswamy, R., Odom, P., Kersting, K., Leake, D., & Natarajan, S., Transfer Learning Across Relational and Uncertain Domains: A Language-Bias Approach, International Workshop on Statistical Relational AI (StarAI) 2015.
Yang, S., Kersting, K., Terry, G., Carr, J., & Natarajan, S., Modeling Coronary Artery Calcification Levels From Behavioral Data in a Clinical Study, Artificial Intelligence in Medicine (AIME) 2015.
Odom, P., Bangera, V., Khot, T., Page, D., & Natarajan, S., Extracting Adverse Drug Events from Text using Human Advice, Artificial Intelligence in Medicine (AIME) 2015.
Odom, P., Khot, T., Porter, R., & Natarajan, S., Knowledge-Based Probabilistic Logic Learning, Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI) 2015.
Weiss, J., Natarajan, S., & Page, D., Learning To Reject Sequential Importance Steps for Continuous-Time Bayesian Networks, Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI) 2015.
Odom, P., Khot, T., & Natarajan, S., Learning Probabilistic Logic Models with Human Advice, AAAI Spring Symposium on Knowledge Representation and Reasoning 2015.
Odom, P., & Natarajan, S., Active Advice Seeking for Inverse Reinforcement Learning, AAAI Student Abstract and Poster Program (AAAI) 2015.

2014
Poyrekar, S., Natarajan, S., & Kersting, K., A Deeper Empirical Analysis of CBP algorithm: Grounding is the Bottleneck, International Workshop on Statistical Relational AI (StarAI) 2014.
Khot, T., Natarajan, S., Kersting, K., Gutmann, B., & Shavlik, J., Gradient-based Boosting for Statistical Relational Learning: The Markov Logic Network and Missing Data Cases, Machine Learning Journal (MLJ) 2014.
Yang, S., Khot, T., Kersting, K., Kunapuli, G., Hauser, K., & Natarajan, S., Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach, International Conference on Data Mining (ICDM) 2014.
Khot, T., Natarajan, S., & Shavlik, J., Relational One-Class Classification: A non-parametric approach, Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI) 2014.
Natarajan, S., Leiva, J.M.P., Khot, T., Kersting, K., Re, C., & Shavlik, J., Effectively creating weakly labeled training examples via approximate domain knowledge, International Conference in Inductive Logic Programming (ILP) 2014.
Poole, D., Buchman, D., Kazemi, S.M., Kersting, K., & Natarajan, S., Population Size Extrapolation in Relational Probabilistic Modelling, Scalable Uncertainty Management (SUM) 2014.
Fern, A., Natarajan, S., Judah, K., & Tadepalli, P., A Decision-Theoretic Model of Assistance, Journal Of Artificial Intelligence Research (JAIR) 2014.
Kazemi, S.M., Buchman, D., Kersting, K., Natarajan, S., & Poole, D., Relational Logistic Regression, International Conference on Principles of Knowledge Representation and Reasoning (KR) 2014.
Magnano, C., Soni, A., Natarajan, S., & Kunapuli, G., A graphical model approach to ATLAS-free mining of MRI images, SIAM International Conference on Data Mining (SDM) 2014.

2013
Ahmadi, B., Kersting, K., Mladenov, M., & Natarajan, S., Exploring Symmetries for Scaling Loopy Belief Propagation and Relational Training, Machine Learning Journal (MLJ) 2013.
Natarajan, S., Saha, B.N., Joshi, S., Edwards, A., Moody, E., Khot, T., Kersting, K., Whitlow, C.T., & Maldjian, J.A., Relational Learning helps in Three-way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain (draft), International Journal of Machine Learning and Cybernetics, Springer 2013.
Kunapuli, G., Odom, P., Shavlik, J., & Natarajan, S., Guiding Autonomous Agents to Better Behaviors through Human Advice, IEEE International Conference on Data Mining (ICDM) 2013.
Natarajan, S., Kersting, K., Ip, E., Jacobs, D., & Carr, J., Early Prediction of Coronary Artery Calcification Levels Using Machine Learning, AAAI conference on Innovative Applications in AI (IAAI) 2013.
Saha, B., Kunapuli, G., Ray, N., Maldjian, J., & Natarajan, S., AR-Boost: Reducing Overfitting by a Robust Data-Driven Regularization Strategy, European Conference on Machine Learning, (ECMLPKDD) 2013.
Natarajan, S., Odom, P., Joshi, S., Khot, T., Kersting, K., & Tadepalli, P., Accelarating Imitation Learning in Relational Domains via Transfer by Initialization, International Conference on Inductive Logic Programming (ILP) 2013.
Khot, T., Natarajan, S., Kersting, K., & Shavlik, J., Learning Relational Probabilistic Models from Partially Observed Data - Opening the Closed-World Assumption, International Conference on Inductive Logic Programming (ILP) 2013.
Weiss, J., Natarajan, S., & Page, D., Learning When to Reject an Importance Sample, Late-Breaking Paper (AAAI) 2013.

2012
Weiss, J., Natarajan, S., Peissig, P., McCarty, C., & Page, D., Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records, AI Magazine 2012.
Weiss, J., Natarajan, S., & Page, D., Multiplicative Forests for Continuous-Time Processes, Neural Information Processing Systems (NIPS) 2012.
Ahmadi, B., Kersting, K., & Natarajan, S., Lifted Online Training of Relational Models with Stochastic Gradient Methods, European Conference on Machine Learning, (ECMLPKDD) 2012.
Natarajan, S., Kersting, K., Joshi, S., Saldana, S., Ip, E., Jacobs, D., & Carr, J., Early Prediction of Coronary Artery Calcification Levels Using Statistical Relational Learning, ICML Workshop on Machine Learning for Clinical Data Analysis 2012.
Weiss, J., Natarajan, S., Peissig, P., McCarty, C., & Page, D., Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records, AAAI conference on Innovative Applications in AI (IAAI) 2012.
Page, D., Natarajan, S., Costa, V.S., Peissig, P., Barnard, A., & Caldwell, M., Identifying Adverse Drug Events from Multi-Relational Healthcare Data, Twenty-Sixth Conference on Artificial Intelligence (AAAI) 2012.
Saha, B.N., Natarajan, S., Kota, G., Whitlow, C.T., Bowden, D.W., Divers, J., Freedman, B.I., & Maldjian, J.A., A Novel Hierarchical Level Set with AR-Boost for White Matter Lesion Segmentation in Diabetes, International Conference on Machine Learning and Applications (ICMLA) 2012.
Natarajan, S., Joshi, S., Saha, B.N., Edwards, A., Moody, E., Khot, T., Kersting, K., Whitlow, C.T., & Maldjian, J.A., A Machine Learning Pipeline for Three-way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain, International Conference on Machine Learning and Applications (ICMLA) 2012.
Saha, B.N., Whitlow, C.T., Kota, G., Moody, E., Natarajan, S., Bowden, D.W., Divers, J., Freedman, B.I., & Maldjian, J.A., Hierarchical Level Sets with Boosting for White Matter Lesion Segmentation in Diabetes, Radiological Society of North America Annual Meeting 2012.
Maldjian, J.A., Whitlow, C.T., Saha, B.N., Kota, G., Moody, E., Bowden, D.W., Divers, J., & Freedman, B.I., Evaluation of Automated White Matter Lesion Segmentation in Diabetes, Radiological Society of North America Annual Meeting 2012.
Ahmadi, B., Kersting, K., & Natarajan, S., Lifted Parameter Learning in Relational Models, ICML Workshop on Statistical Relational Learning (SRL) 2012.
Khot, T., Natarajan, S., Kersting, K., & Shavlik, J., Structure Learning with Hidden Data in Relational Domains, ICML Workshop on Statistical Relational Learning (SRL) 2012.
Natarajan, S., Odom, P., Joshi, S., Khot, T., Kersting, K., & Tadepalli, P., Accelarating Imitation Learning in Relational Domains via Transfer by Initialization, International Workshop on Statistical Relational AI 2012.
Freedman, R.G., Braz, R.d.S., Bui, H., & Natarajan, S., Initial Empirical Evaluation of Anytime Lifted Belief Propagation, International Workshop on Statistical Relational AI 2012.
Khot, T., Srivastava, S., Natarajan, S., & Shavlik, J., Learning Relational Structure for Temporal Relation Extraction, International Workshop on Statistical Relational AI 2012.
N, P.K.V., Manimaran, S.S., Ravindran, B., & Natarajan, S., Integrating Human Instructions and Reinforcement Learners: An SRL Approach, International Workshop on Statistical Relational AI 2012.
Poole, D., Buchman, D., Natarajan, S., & Kersting, K., Aggregation and Population Growth: The Relational Logistic Regression and Markov Logic Cases, International Workshop on Statistical Relational AI 2012.

2011
Natarajan, S., Khot, T., Kersting, K., Gutmann, B., & Shavlik, J., Gradient-based Boosting for Statistical Relational Learning: The Relational Dependency Network Case, Invited contribution to special issue of Machine Learning Journal (MLJ) 2011.
Natarajan, S., Tadepalli, P., & Fern, A., A Relational Hierarchical Model of Decision-Theoretic Assistance, Knowledge and Information Systems (KAIS) 2011.
Natarajan, S., Joshi, S., Tadepalli, P., Kersting, K., & Shavlik, J., Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach, International Joint Conference in AI (IJCAI) 2011.
Khot, T., Natarajan, S., Kersting, K., & Shavlik, J., Learning Markov Logic Networks via Functional Gradient Boosting, International Conference in Data Mining (ICDM) 2011.
Subramaniam, S., Natarajan, S., & Senes, A., A Machine Learning based Approach to Improve Protein Sidechain Optimization, ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB) 2011.
Natarajan, S., Joshi, S., Tadepalli, P., Kersting, K., & Shavlik, J., Imitation Learning in Relational Domains Using Functional Gradient Boosting, The Learning Workshop 2011.

2010
Natarajan, S., & Page, D., Machine Learning for High-Throughput Biomedical Data: Lessons Learned, Machine Learning Encyclopedia 2010.
Natarajan, S., Khot, T., Lowd, D., Kersting, K., Tadepalli, P., & Shavlik, J., Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models, European Conference on Machine Learning (ECML) 2010.
Natarajan, S., Khot, T., Kersting, K., Gutmann, B., & Shavlik, J., Boosting Relational Dependency Networks, International Conference on Inductive Logic Programming (ILP) 2010.
Natarajan, S., Kunapuli, G., Judah, K., Tadepalli, P., Kersting, K., & Shavlik, J., Multi Agent Inverse Reinforcement Learning, IEEE Conference on Machine Learning and Applications (ICMLA) 2010.
Walker, T., Kunapuli, G., Natarajan, S., Shavlik, J., & Page, D., Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge, International Conference on Inductive Logic Programming (ILP) 2010.
Natarajan, S., Kunapuli, G., Judah, K., Tadepalli, P., Kersting, K., & Shavlik, J., Multi-Agent Inverse Reinforcement Learning, The Learning Worshop 2010.

2009
Natarajan, S., Tadepalli, P., Dietterich, T.G., & Fern, A., Learning First-Order Probabilistic Models with Combining Rules, Annals of Mathematics and AI, Special Issue on Probabilistic Relational Learning 2009.
Shavlik, J., & Natarajan, S., Speeding up Inference in Markov Logic Networks By Preprocessing to Reduce the Size of the Resulting Grounded Network, International Joint Conference in Artificial Intelligence (IJCAI) 2009.
Natarajan, S., Tadepalli, P., Kunapuli, G., & Shavlik, J., Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule, IEEE Conference on Machine Learning and Applications (ICML-A) 2009.
Kersting, K., Ahmadi, B., & Natarajan, S., Counting Lifted Belief Propagation, International Conference on Uncertainty in AI (UAI) 2009.
Natarajan, S., Kunapuli, G., Reilly, C.O., Maclin, R., Walker, T., Page, D., & Shavlik, J., ILP for Bootstrapped Learning: A Layered Approach to Automating the ILP Setup Problem, International Conference on Inductive Logic Programming 2009.
Natarajan, S., Tadepalli, P., Kunapuli, G., & Shavlik, J., Knowledge Intensive Learning: Directed vs. Undirected SRL Models, International Workshop in SRL 2009.
Braz, R.d.S., Natarajan, S., Bui, H., Shavlik, J., & Russell, S., Anytime Lifted Belief Propagation, International Workshop in SRL 2009.

2008
Mehta, N., Natarajan, S., Tadepalli, P., & Fern, A., Transfer in Variable Reward Hierarchical Reinforcement Learning, Invited contribution to Inductive transfer in Machine Learning 2008.
Natarajan, S., H.Bui, H., Tadepalli, P., Kersting, K., & Wong, W., Logical Hierarchical Hidden Markov Models for User Activity Recognition, International Conference on Inductive Logic Programming 2008.

2007
Natarajan, S., Tadepalli, P., & Fern, A., A Relational Hierarchical Model of Decision-Theoretic Assistance, Proceedings of the International Conference on Inductive Logic Programming 2007.
Fern, A., Natarajan, S., Judah, K., & Tadepalli, P., A Decision theoretic model of Assistance, International Joint Conference in Artificial Intelligence (IJCAI) 2007.
Natarajan, S., Judah, K., Tadepalli, P., & Fern, A., A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open Problems, AAAI Spring Symposium on Interaction Challenges for Intelligent Assistants 2007.
Natarajan, S., Tadepalli, P., & Fern, A., Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies - Extended Abstract, Proceedings of the Dagstuhl Seminar on Probabilistic, Logical and Relational Learning 2007.

2006
Fern, A., Natarajan, S., Judah, K., & Tadepalli, P., A Decision theoretic model of Assistance, Modeling Others from Observations workshop in AAAI 2006.
Natarajan, S., Wong, W., & Tadepalli, P., Structure Refinement in First Order Conditional Influence Language, Open Problems in Statistical Relational Learning, ICML 2006.

2005
Natarajan, S., Tadepalli, P., Altendorf, E., Dietterich, T.G., Fern, A., & Restificar, A., Learning First-Order Probabilistic Models with Combining Rules, 22nd International Conference on Machine Learning (ICML) 2005.
Natarajan, S., & Tadepalli, P., Dynamic Preferences in Multi-Criteria Reinforcement Learning, 22nd International Conference on Machine Learning (ICML) 2005.