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Deepak Venugopal Publications

Dissertation

  • Deepak Venugopal, "Scalable Inference Techniques for Markov logic", Ph.D. thesis, University of Texas at Dallas, 2015. [pdf]

Conference Papers

  1. Somdeb Sarkhel, Deepak Venugopal, Tuan Anh Pham, Parag Singla and Vibhav Gogate, “Scalable Training of Markov Logic Networks using Approximate Counting,” AAAI 2016. [pdf] [extended-version]

  2. Deepak Venugopal, Somdeb Sarkhel and Vibhav Gogate, Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs, In 29th AAAI Conference on Artificial Intelligence (AAAI), 2015. [pdf]

  3. Deepak Venugopal and Vibhav Gogate, Scaling-up Importance Sampling for Markov Logic Networks, In 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014. [pdf]

  4. Somdeb Sarkhel, Deepak Venugopal, Parag Singla and Vibhav Gogate, An Integer Polynomial Programming Based Framework for Lifted MAP Inference, In 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014. [pdf]

  5. Deepak Venugopal, Chen Chen, Vibhav Gogate and Vincent Ng, Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features, In Empirical Methods in Natural Language Processing Conference (EMNLP), 2014. [pdf]

  6. Deepak Venugopal and Vibhav Gogate, Evidence-Based Clustering for Scalable Inference in Markov Logic, In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), 2014. [pdf]

  7. Somdeb Sarkhel, Deepak Venugopal, Parag Singla and Vibhav Gogate, Lifted MAP Inference for Markov Logic Networks, In 17th International Conference on Artificial Intelligence and Statistics (AISTATS), 2014. [pdf]

  8. Deepak Venugopal and Vibhav Gogate, Dynamic Blocking and Collapsing for Gibbs Sampling, In 29th Conference on Uncertainty in Artificial Intelligence (UAI), 2013. [pdf]

  9. Deepak Venugopal and Vibhav Gogate, GiSS: Combining Gibbs Sampling and SampleSearch for Inference in Mixed Probabilistic and Deterministic Graphical Models, In 27th AAAI Conference on Artificial Intelligence (AAAI), 2013. [pdf]

  10. Deepak Venugopal and Vibhav Gogate, On Lifting the Gibbs Sampling Algorithm, In 26th Annual Conference on Neural Information Processing Systems (NIPS), 2012. [pdf]

  11. Vibhav Gogate, Abhay Jha and Deepak Venugopal, Advances in Lifted Importance Sampling, In 26th AAAI Conference on Artificial Intelligence (AAAI), 2012. [pdf]

Peer-Reviewed Workshop Papers

  1. Deepak Venugopal, Scaling-up Inference in Markov Logic, Extended Abstract, In AAAI-15 Doctoral Consortium, 2015. [pdf]

  2. Deepak Venugopal and Vibhav Gogate, Evidence-Based Clustering for Scalable Inference in Markov Logic, In AAAI-14 Workshop on Statistical Relational Artificial Intelligence, 2014.

  3. Deepak Venugopal and Vibhav Gogate, On Lifting the Gibbs Sampling Algorithm, In UAI-12 Workshop on Statistical Relational Artificial Intelligence, 2012.