Dr. Vibhav Gogate

Associate Professor

Co-Director of the Center for Machine Learning

Degrees:

• Ph.D., Computer Science, University of California, Irvine, 2009
• M.S. in Computer Science, University of Maine, Orono, 2002
• B.S. in Computer Engineering, University of Mumbai, Maharashtra, India, 1999

Research Interests:

• Machine learning
• Artificial Intelligence
• Data mining
• Big data

Major Honors and Awards:

Representative Publications:

• Rahman and V. Gogate, “Merging strategies for sum-product networks: From trees to graphs,” In Proceedings of the Thirty-Second Conference Conference on Uncertainty in Artificial Intelligence, pages 617–626, 2016.
• de Salvo Braz, C. O’Reilly, V. Gogate, and R. Dechter, “Probabilistic infer- ence modulo theories,” In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, pages 3591–3599, 2016.
• Rahman and V. Gogate, “Learning ensembles of cutset networks,” In AAAI conference on Artificial Intelligence, pages 3301–3307, 2016.
• Sarkhel, D. Venugopal, T. A. Pham, P. Singla, and V. Gogate, “Scalable training of markov logic networks using approximate counting,” In AAAI conference on Artificial Intelligence, pages 1067–1073, 2016.
• Chou, S. Sarkhel, N. Ruozzi, and V. Gogate, “On parameter tying by quantization,” In AAAI conference on Artificial Intelligence, pages 3241–3247, 2016.
• Deepak Venugopal, Somdeb Sarkhel and Vibhav Gogate, “Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs,” In AAAI 2015.
• Somdeb Sarkhel, Deepak Venugopal, Parag Singla and Vibhav Gogate, “An Integer Polynomial Programming Based Framework for Lifted MAP Inference,” In NIPS 2014.
• 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.
• Happy Mittal, Prasoon Goyal, Vibhav Gogate and Parag Singla, “New Rules for Domain Independent Lifted MAP Inference,” In NIPS 2014.
• Deepak Venugopal and Vibhav Gogate, “Scaling-up Importance Sampling for Markov Logic Networks,” In NIPS 2014.