Peter Orbanz
Peter Orbanz
Verified email at stat.columbia.edu - Homepage
Title
Cited by
Cited by
Year
Encyclopedia of machine learning
C Sammut, GI Webb
Springer Science & Business Media, 2011
8422011
Bayesian Nonparametric Models.
P Orbanz, YW Teh
Encyclopedia of machine learning, 2010
2112010
Bayesian models of graphs, arrays and other exchangeable random structures
P Orbanz, DM Roy
IEEE transactions on pattern analysis and machine intelligence 37 (2), 437-461, 2014
1852014
Nonparametric Bayesian image segmentation
P Orbanz, JM Buhmann
International Journal of Computer Vision 77 (1-3), 25-45, 2008
1312008
Cluster analysis of heterogeneous rank data
LM Busse, P Orbanz, JM Buhmann
Proceedings of the 24th international conference on Machine learning, 113-120, 2007
1292007
Random function priors for exchangeable arrays with applications to graphs and relational data
J Lloyd, P Orbanz, Z Ghahramani, DM Roy
Advances in Neural Information Processing Systems, 998-1006, 2012
1012012
Dependent Indian buffet processes
S Williamson, P Orbanz, Z Ghahramani
Proceedings of the thirteenth international conference on artificial …, 2010
572010
Non-vacuous generalization bounds at the imagenet scale: a PAC-Bayesian compression approach
W Zhou, V Veitch, M Austern, RP Adams, P Orbanz
arXiv preprint arXiv:1804.05862, 2018
442018
Smooth image segmentation by nonparametric Bayesian inference
P Orbanz, JM Buhmann
European conference on computer vision, 444-457, 2006
352006
Distribution theory for hierarchical processes
F Camerlenghi, A Lijoi, P Orbanz, I Prünster
The Annals of Statistics 47 (1), 67-92, 2019
342019
Construction of nonparametric Bayesian models from parametric Bayes equations
P Orbanz
Advances in neural information processing systems, 1392-1400, 2009
272009
Random‐walk models of network formation and sequential Monte Carlo methods for graphs
B Bloem‐Reddy, P Orbanz
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2018
172018
Lecture Notes on Bayesian Nonparametrics
P Orbanz
162014
Compressibility and generalization in large-scale deep learning
W Zhou, V Veitch, M Austern, RP Adams, P Orbanz
132018
Subsampling large graphs and invariance in networks
P Orbanz
arXiv preprint arXiv:1710.04217, 2017
122017
SAR images as mixtures of Gaussian mixtures
P Orbanz, JM Buhmann
IEEE International Conference on Image Processing 2005 2, II-209, 2005
122005
Unit–rate Poisson representations of completely random measures
P Orbanz, S Williamson
112011
Projective limit random probabilities on Polish spaces
P Orbanz
Electronic Journal of Statistics 5, 1354-1373, 2011
9*2011
Preferential attachment and vertex arrival times
B Bloem-Reddy, P Orbanz
arXiv preprint arXiv:1710.02159, 2017
82017
Music preference learning with partial information
Y Moh, P Orbanz, JM Buhmann
2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008
82008
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