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2005 2006 2007 2008 2009 2010 2011 2012Jeremy Weiss, Sriraam Natarajan, Peggy Peissig, Catherine McCarty and David Page, Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records, AI Magazine 2012.
Jeremy Weiss, Sriraam Natarajan and David Page. Multiplicative Forests for Continuous-Time Processes. Neural Information Processing Systems (NIPS), 2012.
Babak Ahmadi, Kristian Kersting and Sriraam Natarajan. Lifted Online Training of Relational Models with Stochastic Gradient Methods. ECML-PKDD, 2012.
Sriraam Natarajan, Kristian Kersting, Saket Joshi, Santiago Saldana, Edward Ip, David Jacobs and Jeffery Carr. Early Prediction of Coronary Artery Calcification Levels Using Statistical Relational Learning. ICML Workshop on Machine Learning for Clinical Data Analysis, 2012.
Jeremy Weiss, Sriraam Natarajan, Peggy Peissig, Catherine McCarty and David Page. Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records. AAAI conference on Innovative Applications in AI (IAAI), 2012.
David Page, Sriraam Natarajan, Vitor Santos Costa, Peggy Peissig, Aubrey Barnard, and Michael Caldwell. Identifying Adverse Drug Events from Multi-Relational Healthcare Data. Twenty-Sixth Conference on Artificial Intelligence, AAAI-12.
Baidya N. Saha, Sriraam Natarajan, Gopi Kota, Christopher T. Whitlow, Donald W. Bowden, Jasmin Divers, Barry I. Freedman and Joseph A. Maldjian. A Novel Hierarchical Level Set with AR-Boost for White Matter Lesion Segmentation in Diabetes. International Conference on Machine Learning and Applications (ICMLA), 2012.
Sriraam Natarajan, Saket Joshi, Baidya N. Saha, Adam Edwards, Elizabeth Moody, Tushar Khot, Kristian Kersting, Christopher T. Whitlow and Joseph A. Maldjian. 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.
Baidya N. Saha, Christopher T. Whitlow, Gopi Kota, Elizabeth Moody, Sriraam Natarajan, Donald W. Bowden, Jasmin Divers, Barry I. Freedman and Joseph A. Maldjian. Hierarchical Level Sets with Boosting for White Matter Lesion Segmentation in Diabetes. Radiological Society of North America Annual Meeting, 2012.
Joseph A. Maldjian, Christopher T. Whitlow, Baidya N. Saha, Gopi Kota, Elizabeth Moody, Donald W. Bowden, Jasmin Divers and Barry I. Freedman. Evaluation of Automated White Matter Lesion Segmentation in Diabetes. Radiological Society of North America Annual Meeting, 2012.
Babak Ahmadi, Kristian Kersting and Sriraam Natarajan. Lifted Parameter Learning in Relational Models. ICML Workshop on Statistical Relational Learning (SRL), 2012.
Tushar Khot, Sriraam Natarajan, Kristian Kersting and Jude Shavlik. Structure Learning with Hidden Data in Relational Domains. ICML Workshop on Statistical Relational Learning (SRL), 2012.
Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting and Prasad Tadepalli. Accelarating Imitation Learning in Relational Domains via Transfer by Initialization. International Workshop on Statistical Relational AI, 2012.
Richard G. Freedman, Rodrigo de Salvo Braz, Hung Bui and Sriraam Natarajan. Initial Empirical Evaluation of Anytime Lifted Belief Propagation. International Workshop on Statistical Relational AI, 2012.
Tushar Khot, Siddharth Srivastava, Sriraam Natarajan and Jude Shavlik. Learning Relational Structure for Temporal Relation Extraction. International Workshop on Statistical Relational AI, 2012.
Pradyot Korupolu V N, S S Manimaran, Balaraman Ravindran and Sriraam Natarajan. Integrating Human Instructions and Reinforcement Learners : An SRL Approach. International Workshop on Statistical Relational AI, 2012.
David Poole, David Buchman, Sriraam Natarajan and Kristian Kersting. Aggregation and Population Growth: The Relational Logistic Regression and Markov Logic Cases. International Workshop on Statistical Relational AI, 2012.
Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann and Jude Shavlik. Gradient-based Boosting for Statistical Relational Learning: The Relational Dependency Network Case, Invited contribution to special issue of Machine Learning Journal (MLJ), 2011.
Sriraam Natarajan, Prasad Tadepalli and Alan Fern, A Relational Hierarchical Model of Decision-Theoretic Assistance Knowledge and Information Systems(KAIS) 2011 - To appear.
Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, and Jude Shavlik. Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach , International Joint Conference in AI (IJCAI) 2011.
Tushar Khot, Sriraam Natarajan, Kristian Kersting, and Jude Shavlik. Learning Markov Logic Networks via Functional Gradient Boosting, International Conference in Data Mining (ICDM) 2011.
Sabareesh Subramaniam, Sriraam Natarajan, and Alessandro Senes. A Machine Learning based Approach to Improve Protein Sidechain Optimization, ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB) 2011.
Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, and Jude Shavlik Imitation Learning in Relational Domains Using Functional Gradient Boosting , The Learning Workshop 2011.
Sriraam Natarajan and David Page. Machine Learning for High-Throughput Biomedical Data: Lessons Learned . Machine Learning Encyclopedia, 2010.
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Kristian Kersting, Prasad Tadepalli and Jude Shavlik. Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models , European Conference on Machine Learning (ECML) 2010. (Acceptance Rate 18%).
Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann and Jude Shavlik. Boosting Relational Dependency Networks, International Conference on Inductive Logic Programming (ILP) 2010.
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting and Jude Shavlik. Multi Agent Inverse Reinforcement Learning, IEEE Conference on Machine Learning and Applications (ICMLA) 2010.
Trevor Walker, Gautam Kunapuli, Sriraam Natarajan, Jude Shavlik and David Page. Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge , International Conference on Inductive Logic Programming (ILP) 2010.
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting and Jude Shavlik. Multi-Agent Inverse Reinforcement Learning The Learning Worshop - 2010.
Sriraam Natarajan,Prasad Tadepalli, Thomas G. Dietterich and Alan Fern. Learning First-Order Probabilistic Models with Combining Rules . Annals of Mathematics and AI, Special Issue on Probabilistic Relational Learning 2009.
Jude Shavlik, Sriraam Natarajan. 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. (Acceptance Rate 25.7%)
Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapuli, Jude Shavlik. Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule, IEEE Conference on Machine Learning and Applications (ICML-A) 2009.
Kristian Kersting, Babak Ahmadi, Sriraam Natarajan. Counting Lifted Belief Propagation , International Conference on Uncertainty in AI (UAI) 2009.
Sriraam Natarajan, Gautam Kunapuli, Ciaran O' Reilly, Rich Maclin, Trevor Walker, David Page, and Jude Shavlik. ILP for Bootstrapped Learning: A Layered Approach to Automating the ILP Setup Problem , International Conference on Inductive Logic Programming 2009.
Sriraam Natarajan, Prasad Tadepalli Gautam Kunapuli and Jude Shavlik. Knowledge Intensive Learning: Directed vs. Undirected SRL Models. International Workshop in SRL 2009.
Rodrigo De Salvo Braz, Sriraam Natarajan, Hung Bui, Jude Shavlik, and Stuart Russell. Anytime Lifted Belief Propagation. International Workshop in SRL 2009.
Neville Mehta, Sriraam Natarajan, Prasad Tadepalli and Alan Fern. Transfer in Variable Reward Hierarchical Reinforcement Learning. Invited contribution to Inductive transfer in Machine Learning, Springer Verlag publications, 2008.
Sriraam Natarajan, Hung H.Bui, Prasad Tadepalli, Kristian Kersting, Weng-Keen Wong. Logical Hierarchical Hidden Markov Models for User Activity Recognition , International Conference on Inductive Logic Programming 2008. (Acceptance Rate 27%)
Sriraam Natarajan, Prasad Tadepalli and Alan Fern. A Relational Hierarchical Model of Decision-Theoretic Assistance. Proceedings of the International Conference on Inductive Logic Programming, (ILP 2007). (Acceptance Rate 25%)
Alan Fern, Sriraam Natarajan, Kshitij Judah and Prasad Tadepalli, A Decision theoretic model of Assistance, International Joint Conference in Artificial Intelligence (IJCAI 2007). (Acceptance Rate 18%)
Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli and Alan Fern. A Decision-Theoretic Model of Assistance - Evaluation, Extensions and Open Problems, AAAI 2007 Spring Symposium on Interaction Challenges for Intelligent Assistants, Stanford University, USA.
Sriraam Natarajan, Prasad Tadepalli and Alan Fern. Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies, Extended Abstract in the Proceedings of the Dagstuhl Seminar on Probabilistic, Logical and Relational Learning - A Further Synthesis, (2007).
Alan Fern, Sriraam Natarajan, KshitijJudah and Prasad Tadepalli. A Decision theoretic model of Assistance, Modeling Others from Observations workshop in AAAI 2006.
Sriraam Natarajan, Weng-Keen Wong and Prasad Tadepalli, Structure Refinement in First Order Conditional Influence Language, Open Problems in Statistical Relational Learning, ICML 2006.
Sriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern and Angelo Restificar. Learning First-Order Probabilistic Models with Combining Rules. The 22nd International Conference on Machine Learning (ICML 2005). (Acceptance Rate 27%)
Sriraam Natarajan and Prasad Tadepalli. Dynamic Preferences in Multi-Criteria Reinforcement Learning.The 22nd International Conference on Machine Learning (ICML 2005). (Acceptance Rate 27%)