Publications with keyword "Graphical models"
| 1. | S. Ravanbakhsh, B. Poczos, R. Greiner. "Boolean matrix factorization and noisy completion via message passing". International Conference on Machine Learning (ICML), (ed: Maria Florina Balcan, Kilian Q. Weinberger), pp 945-954, June 2016.  |
| 2. | S. Ravanbakhsh, B. Poczos, J. Schneider, D. Schuurmans, R. Greiner. "Stochastic Neural Networks with Monotonic Activation Functions". Artificial Intelligence and Statistics, (ed: Arthur Gretton, Christian C. Robert), pp 809-818, May 2016.  |
| 3. | S. Ravanbakhsh, R. Greiner, B. Frey, C. Srinivasa. "Min-Max Problems on Factor-Graphs". International Conference on Machine Learning (ICML), pp 1035-1043, June 2014. |
| 4. | S. Ravanbakhsh, R. Greiner, B. Frey. "Training Restricted Boltzmann Machines by Perturbation". NIPS 2013 Workshop: Perturbations, Optimization and Statistics, abs/1405.1436, pp n/a, December 2013. |
| 5. | S. Ravanbakhsh, C. Yu, R. Greiner. "A Generalized Loop Correction Method for Approximate Inference in Graphical Models". International Conference on Machine Learning (ICML), (ed: John Langford, Joelle Pineau), pp 543-550, July 2012. |
| 6. | A. Ihler, S. Kirshner, M. Ghil, A. Robertson, P. Smyth. "Graphical models for statistical inference and data assimilation". Physica D: Nonlinear Phenomena, June 2007. |
| 7. | T. Caetano, T. Caelli, D. Schuurmans, D. Barone. "Graphical Models and Point Pattern Matching". IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(10), January 2006. |
| 8. | R. Greiner, X. Su, B. Shen, W. Zhou. "Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers". Machine Learning Journal (MLJ), (ed: P. Larranaga, J.A. Lozano, J.M. Pena, I. Inza), 59(3), pp 297--322, June 2005. |
| 9. | B. Shen, X. Su, R. Greiner, P. Musilek, C. Cheng. "Discriminative Parameter Learning of General Bayesian Network Classifiers". Fifteenth IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Sacramento, California, November 2003. |
| 10. | T. Van Allen, R. Greiner, P. Hooper. "Bayesian Error-Bars for Belief Net Inference". Conference on Uncertainty in Artificial Intelligence (UAI), Seattle, Washington, USA, August 2001.  |
| 11. | J. Cheng, R. Greiner. "Learning Bayesian Belief Network Classifiers: Algorithms and System". Canadian Conference on Artificial Intelligence (CAI), Ottawa, Canada, May 2001. |
| 12. | T. Van Allen, R. Greiner. "A Model Selection Criteria for Learning Belief Nets: An Empirical Comparison". International Conference on Machine Learning (ICML), Stanford University, July 2000. |
| 13. | R. Greiner, W. Zhou. "Learning Accurate Belief Nets using Explicitly-Labeled Queries". Conditional Independence Structures and Graphical Models, Toronto, September 1999. |
