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Peter Orbanz
Peter Orbanz
Bestätigte E-Mail-Adresse bei stat.columbia.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Bayesian nonparametric models.
P Orbanz, YW Teh
Encyclopedia of machine learning 1, 81-89, 2010
3132010
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
3002014
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
2062018
Nonparametric Bayesian image segmentation
P Orbanz, JM Buhmann
International Journal of Computer Vision 77, 25-45, 2008
1702008
Cluster analysis of heterogeneous rank data
LM Busse, P Orbanz, JM Buhmann
Proceedings of the 24th international conference on Machine learning, 113-120, 2007
1502007
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 25, 2012
1412012
Distribution theory for hierarchical processes
F Camerlenghi, A Lijoi, P Orbanz, I Prünster
972019
Dependent Indian buffet processes
S Williamson, P Orbanz, Z Ghahramani
Proceedings of the thirteenth international conference on artificial …, 2010
662010
Smooth image segmentation by nonparametric Bayesian inference
P Orbanz, JM Buhmann
Computer Vision–ECCV 2006: 9th European Conference on Computer Vision, Graz …, 2006
412006
Construction of nonparametric Bayesian models from parametric Bayes equations
P Orbanz
Advances in neural information processing systems 22, 2009
332009
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
322018
Lecture Notes on Bayesian Nonparametrics
P Orbanz
322014
Subsampling large graphs and invariance in networks
P Orbanz
arXiv preprint arXiv:1710.04217, 2017
222017
Compressibility and generalization in large-scale deep learning
W Zhou, V Veitch, M Austern, RP Adams, P Orbanz
arXiv preprint arXiv:1804.05862 2, 2018
202018
SAR images as mixtures of Gaussian mixtures
P Orbanz, JM Buhmann
IEEE International Conference on Image Processing 2005 2, II-209, 2005
162005
Method for operating a hearing device
JM Buhmann, S Korl, Y Moh, P Orbanz
US Patent 8,477,972, 2013
152013
Limit theorems for distributions invariant under groups of transformations
M Austern, P Orbanz
The Annals of Statistics 50 (4), 1960-1991, 2022
142022
Preferential attachment and vertex arrival times
B Bloem-Reddy, P Orbanz
arXiv preprint arXiv:1710.02159, 2017
142017
Empirical risk minimization and stochastic gradient descent for relational data
V Veitch, M Austern, W Zhou, DM Blei, P Orbanz
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
122019
Unit–rate Poisson representations of completely random measures
P Orbanz, S Williamson
122011
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