David Sontag

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Che Z, Purushotham S, Cho K, et al. (2018) Recurrent Neural Networks for Multivariate Time Series with Missing Values. Scientific Reports. 8: 6085
Arora S, Ge R, Halpern Y, et al. (2018) Learning topic models -- provably and efficiently Communications of the Acm. 61: 85-93
Silberman N, Sontag D, Fergus R. (2014) 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
Brenner E, Sontag D. (2013) SparsityBoost: A new scoring function for learning Bayesian network structure Uncertainty in Artificial Intelligence - Proceedings of the 29th Conference, Uai 2013. 112-121
Sontag D, Meshi O, Jaakkola T, et al. (2010) 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
Jaakkola T, Sontag D, Globerson A, et al. (2010) Learning Bayesian network structure using LP relaxations Journal of Machine Learning Research. 9: 358-365
Sontag D, Jaakkola T. (2009) Tree block coordinate descent for MAP in graphical models Journal of Machine Learning Research. 5: 544-551
Sontag D, Jaakkola T. (2009) New outer bounds on the marginal polytope Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference