Publications[Workshops/Conferences/Journals]

2016

2015

  • Tushar Khot, Niranjan Balasubramanian, Eric Gribkoff, Ashish Sabharwal, Peter Clark, Oren Etzioni. Exploring Markov Logic Networks for Question Answering. In EMNLP, 2015
  • Phillip Odom, Vishal Bangera, Tushar Khot, David Page and Sriraam Natarajan. Extracting Adverse Drug Events from Text using Human Advice. In Artificial Intelligence in Medicine (AIME), 2015.
  • Phillip Odom, Tushar Khot, Reid Porter, and Sriraam Natarajan Knowledge-Based Probabilistic Logic Learning. In AAAI, 2015.

    2014

    • Shuo Yang, Tushar Khot, Kristian Kersting, Gautam Kunapuli, Kris Hauser, Sriraam Natarajan. Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach. In ICDM 2014.
    • Tushar Khot, Sriraam Natarajan, Jude Shavlik. Relational One-Class Classification: A Non-Parametric Approach. In AAAI 2014. [pdf]

    2013

    • Tushar Khot, Sriraam Natarajan, Kristian Kersting and Jude Shavlik . Learning Relational Probabilistic Models from Partially Observed Data - Opening the Closed-World Assumption. Presented at ILP, 2013. [Invited to special issue of Machine Learning].
    • Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting and Prasad Tadepalli. Accelarating Imitation Learning in Relational Domains via Transfer by Initialization. In ILP, 2013. [To appear].
    • Sriraam Natarajan, Baidya N. Saha, Saket Joshi, Adam Edwards, Elizabeth Moody, Tushar Khot, Kristian Kersting, Christopher T. Whitlow and Joseph A. Maldjian. Relational Learning helps in Three-way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain. International Journal of Machine Learning and Cybernetics, Springer 2013.[doi]
    • Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Re and Jude Shavlik. Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text. In StarAI workshop at AAAI 2013. [pdf]

    2012

    • Tushar Khot, Sriraam Natarajan, Kristian Kersting and Jude Shavlik. Structure Learning with Hidden Data in Relational Domains. In SRL Workshop at ICML, 2012.[pdf].
    • Tushar Khot, Siddharth Srivastava, Sriraam Natarajan and Jude Shavlik. Learning Relational Structure for Temporal Relation Extraction. In StarAI workshop at UAI, 2012.[pdf].
    • 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, Volume 86, Number 1, 25-56, 2012. [doi]
    • 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. In ICMLA 2012. [pdf]
    • Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting and Prasad Tadepalli. Accelarating Imitation Learning in Relational Domains via Transfer by Initialization. In StarAI workshop at UAI, 2012.[pdf]

    2011

    • Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude Shavlik.Learning Markov Logic Networks via Functional Gradient Boosting. In ICDM 2011. [pdf]

    2010

    • Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann and Jude Shavlik. Boosting Relational Dependency Networks. In ILP 2010. [pdf]
    • 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. In ECML 2010. [pdf]

    2009

    • Xiaojin Zhu, Zhiting Xu, and Tushar Khot. How creative is your writing? A linguistic creativity measure from computer science and cognitive psychology perspectives. In NAACL 2009 Workshop on Computational Approaches to Linguistic Creativity, 2009. [pdf]
    • Xiaojin Zhu, Andrew B. Goldberg, and Tushar Khot. Some new directions in graph-based semisupervised learning (invited paper). In ICME, Special Session on Semi-Supervised Learning for Multimedia Analysis, 2009. [pdf]