Publications and Patents

Journal:

  • Bayesian feature selection in high-dimensional regression in presence of correlated noise, G. Feldman, A. Bhadra, S. Kirshner, Stat, 3(1): 258-272, August 2014 (Wiley Online Library)
  • Daily rainfall projections from general circulation models with a downscaling nonhomogeneous hidden Markov model (NHMM) for southeastern Australia, G. Fu, S.P. Charles, S. Kirshner, Hydrological Processes, 27(25):3663-3673, December 2013 (Wiley Online Library)
  • Probabilistic assessment of drought characteristics using a hidden Markov model, G. Mallya, S. Tripathi, S. Kirshner, R.S. Govindaraju, Journal of Hydrological Engineering, 18(7):834-845, July 2013 (ASCE Library)
  • Modelling runoff with statistically downscaled daily site, gridded and catchment rainfall series, G. Fu, S.P. Charles, F.H.S. Chiew, J. Teng, H. Zheng, A.J. Frost, W. Liu, S. Kirshner, Journal of Hydrology, 492:254-265, June 2013 (ScienceDirect)
  • Analysis of Indian monsoon daily rainfall on subseasonal to multidecadal time scales using a hidden Markov model, A.M. Greene, A.W. Robertson, S. Kirshner, Quarterly Journal of Royal Meteorological Society, 134(633):875-887, April 2008 (Wiley InterSciencepreprint)
  • Graphical models for statistical inference and data assimilation, A.T. Ihler, S. Kirshner, M. Ghil, A.W. Robertson, P. Smyth, Physica D (special issue on Data Assimilation), 230(1-2):72-87, June 2007 (ScienceDirectpreprint)
  • Subseasonal-to-interdecadal variability of the Australian monsoon over North Queensland, A.W. Robertson, S. Kirshner, P. Smyth, S.P. Charles, B.C. Bates, Quarterly Journal of Royal Meteorological Society, 132(615):519-542, Part B, January 2006 (Wiley InterSciencepreprint)
  • Downscaling of daily rainfall occurrence over Northeast Brazil using a hidden Markov model, A.W. Robertson, S. Kirshner, P. Smyth, Journal of Climate, 17(22):4407-4424, November 2004 (Allen Presspreprinttech report)

Conference (peer-reviewed):
  • A scalable method for exact sampling from Kronecker family models, S. Moreno, J. Pfeiffer, J. Neville, and S. Kirshner, ICDM 2014, December 2014 (paper)
  • Learning mixed Kronecker product graph models with simulated method of moments, S. Moreno, J. Neville, and S. Kirshner, KDD 2013, August 2013 (papertech report)
  • Latent tree copulas, S. Kirshner, Proocedings of the Sixth European Workshop on Probabilistic Graphical Models (PGM 2012), September 2012 (paperslidespostersoftware)
  • REGO: Rank-based estimation of Renyi information using Euclidean graph optimization, B. Póczos, S. Kirshner, Cs. Szepesvári, AISTATS 2010 (paper)
  • ICA and ISA using Schweizer-Wolff measure of dependence, S. Kirshner, B. Póczos, Proceedings of the Twenty-Fifth International Conference on Machine Learning, ICML 2008, July 2008 (paperslidessoftware)
  • Learning with tree-averaged densities and distributions, S. Kirshner, Advances in Neural Information Processing Systems, NIPS 2007, December 2007 (paperversion with additional detailsslides)
  • Infinite mixtures of trees, S. Kirshner, P. Smyth, Proceedings of the Twenty-Fourth International Conference on Machine Learning, ICML 2007, June 2007 (paperposterslides)
  • Conditional Chow-Liu tree structures for modeling discrete-valued vector time series, S. Kirshner, P. Smyth, A.W. Robertson, Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence, UAI 2004, July 2004 (papertech reportslides)
  • Unsupervised learning from permuted data, S. Kirshner, S. Parise, P. Smyth, Proceedings of the Twentieth International Conference on Machine Learning, ICML 2003, August 2003 (papertech reportslides)
  • Learning to classify galaxy shapes using the EM algorithm, S. Kirshner, I.V. Cadez, P. Smyth, C. Kamath, Advances in Neural Information Processing Systems 15, NIPS 2002, December 2002, MIT Press, 2003. (paperposter)
  • Probabilistic model-based detection of bent-double radio galaxies, S. Kirshner, I.V. Cadez, P. Smyth, C. Kamath, E. Cantú-Paz, Proceedings of the Sixteenth International Conference on Pattern Recognition, ICPR 2002, August 2002 (papertech reportposter)
  • Adaptivity in agent-based routing for data networks, D.H. Wolpert, S. Kirshner, C.J. Merz, K. Tumer, Fourth International Conference on Automomous Agents, Agents 2000, Barcelona, Spain, June 2000 (paper)
Patents:
  • Modeling of geospatial location over time, S. Kirshner, A. Gray, L. Kite, U.S. Patent Application 15/254,958, filed September 1, 2016 (USPTO)
  • Constructing additive trees monotonic in selected sets of variables, S. Kirshner, U.S. Patent Application 15/178,549, filed June 9, 2016 (USPTO)
  • System and method for using machine learning to generate a model from audited data, A. Gray, S. Kirshner, U.S. Patent Application 15/065,534, filed March 9, 2016 (USPTO)

Proceedings at Workshops (non-reviewed):
  • Generating similar graphs from spherical features, D. Lunga, S. Kirshner, Proceedings of the Ninth Workshop on Mining and Learning with Graphs, MLG 2011, August 2011 (papertech report)
  • Tied Kronecker product graph models to capture variance in network populations, S. Moreno, S. Kirshner, J. Neville, and S.V.N. Vishwanathan, Proceedings of the 48th Annual Allerton Conference on Communications, Control and Computing, 2010 (paper)

Discussions:
  • Comment on article T. Rydén, 'EM versus Markov chain Monte Carlo for estimation of hidden Markov models: a computational perspective', P. Smyth, S. Kirshner, Bayesian Analysis, 3(4):699-705, 2008 (Project Euclid)

Unpublished Technical reports:
  • Estimating densities with non-parametric exponential families, L. Yuan, S. Kirshner, R. Givan, June 2012 (tech report)

Thesis:
  • Modeling of multivariate time series using hidden Markov models, 202 pages, March 2005 (PDFps.gz)