David Sontag - Publications
Affiliations: | Computer Science | New York University, New York, NY, United States |
Area:
Computer ScienceYear | Citation | Score | |||
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2018 | Che Z, Purushotham S, Cho K, Sontag D, Liu Y. Recurrent Neural Networks for Multivariate Time Series with Missing Values. Scientific Reports. 8: 6085. PMID 29666385 DOI: 10.1038/S41598-018-24271-9 | 0.308 | |||
2018 | Arora S, Ge R, Halpern Y, Mimno D, Moitra A, Sontag D, Wu Y, Zhu M. Learning topic models -- provably and efficiently Communications of the Acm. 61: 85-93. DOI: 10.1145/3186262 | 0.351 | |||
2014 | Silberman N, Sontag D, Fergus R. Instance segmentation of indoor scenes using a coverage loss Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8689: 616-631. DOI: 10.1007/978-3-319-10590-1_40 | 0.524 | |||
2013 | Brenner E, Sontag D. SparsityBoost: A new scoring function for learning Bayesian network structure Uncertainty in Artificial Intelligence - Proceedings of the 29th Conference, Uai 2013. 112-121. | 0.309 | |||
2010 | Sontag D, Meshi O, Jaakkola T, Globerson A. More data means less inference: A pseudo-max approach to structured learning Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. | 0.502 | |||
2010 | Jaakkola T, Sontag D, Globerson A, Meila M. Learning Bayesian network structure using LP relaxations Journal of Machine Learning Research. 9: 358-365. | 0.492 | |||
2009 | Sontag D, Jaakkola T. Tree block coordinate descent for MAP in graphical models Journal of Machine Learning Research. 5: 544-551. | 0.451 | |||
2009 | Sontag D, Jaakkola T. New outer bounds on the marginal polytope Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference. | 0.449 | |||
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