Daniel M. Roy

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Gintare Karolina DziugaiteGoogle BrainVerified email at google.com
Joshua B. TenenbaumMITVerified email at mit.edu
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
Vikash K. MansinghkaMIT, Probabilistic Computing ProjectVerified email at mit.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
martin rinardMITVerified email at lcs.mit.edu
Noah D. GoodmanStanford UniversityVerified email at stanford.edu
Cameron E. FreerResearch Scientist, MIT and Project Associate Professor, Keio UniversityVerified email at mit.edu
Balaji LakshminarayananStaff Research Scientist at Google BrainVerified email at google.com
Cristian CadarImperial College LondonVerified email at imperial.ac.uk
Nate AckermanHarvard UniversityVerified email at math.harvard.edu
Jonathan FrankleMassachusetts Institute of TechnologyVerified email at mit.edu
Michael CarbinMassachusetts Institute of TechnologyVerified email at csail.mit.edu
Kallista A. BonawitzGoogleVerified email at google.com
Jeffrey NegreaUniversity of TorontoVerified email at utstat.toronto.edu
Victor VeitchUniversity of Chicago, GoogleVerified email at uchicago.edu
Peter OrbanzColumbia UniversityVerified email at stat.columbia.edu
Mahdi HaghifamPh.D. Candidate, University of TorontoVerified email at mail.utoronto.ca
Hal Daumé IIIAssociate Professor of Computer Science, University of MarylandVerified email at umiacs.umd.edu
James Robert LloydPhD from Machine Learning Group, Cambridge UniversityVerified email at cam.ac.uk

Daniel M. Roy

University of Toronto, Dept of Statistical Sciences; Computer Science

Verified email at utoronto.ca - Homepage

Statistics Theoretical Computer Science Probability Machine Learning Artificial Intelligence


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Church: a language for generative models ND Goodman, VK Mansinghka, D Roy, K Bonawitz, JB Tenenbaum Uncertainty in Artificial Intelligence 22, 23, 2008	893*	2008
Enhancing server availability and security through failure-oblivious computing M Rinard, C Cadar, D Dumitran, DM Roy, T Leu, WS Beebee Jr Proceedings of the 6th conference on Symposium on Opearting Systems Design …, 2004	457	2004
Training generative neural networks via maximum mean discrepancy optimization GK Dziugaite, DM Roy, Z Ghahramani arXiv preprint arXiv:1505.03906, 2015	415	2015
Computing nonvacuous generalization bounds for deep (stochastic) neural networks with many more parameters than training data GK Dziugaite, DM Roy arXiv preprint arXiv:1703.11008, 2017	381	2017
A study of the effect of jpg compression on adversarial images GK Dziugaite, Z Ghahramani, DM Roy arXiv preprint arXiv:1608.00853, 2016	274	2016
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	237	2014
Mondrian forests: Efficient online random forests B Lakshminarayanan, DM Roy, YW Teh Advances in neural information processing systems 27, 3140-3148, 2014	208	2014
The Mondrian process DM Roy, YW Teh Adv. in Neural Inform. Processing Syst 21, 27, 2009	174	2009
A dynamic technique for eliminating buffer overflow vulnerabilities (and other memory errors) M Rinard, C Cadar, D Dumitran, DM Roy, T Leu 20th Annual Computer Security Applications Conference, 82-90, 2004	132	2004
Complexity of Inference in Latent Dirichlet Allocation D Sontag, DM Roy	128*
Bayesian agglomerative clustering with coalescents YW Teh, H Daumé III, D Roy Arxiv preprint arXiv:0907.0781, 2009	127	2009
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, 998-1006, 2012	124	2012
Probabilistically accurate program transformations S Misailovic, D Roy, M Rinard Static Analysis, 316-333, 2011	117	2011
Neural network matrix factorization GK Dziugaite, DM Roy arXiv preprint arXiv:1511.06443, 2015	107	2015
Stabilizing the lottery ticket hypothesis J Frankle, GK Dziugaite, DM Roy, M Carbin arXiv preprint arXiv:1903.01611, 2019	105	2019
Linear mode connectivity and the lottery ticket hypothesis J Frankle, GK Dziugaite, D Roy, M Carbin International Conference on Machine Learning, 3259-3269, 2020	100	2020
The class of random graphs arising from exchangeable random measures V Veitch, DM Roy arXiv preprint arXiv:1512.03099, 2015	89	2015
Data-dependent PAC-Bayes priors via differential privacy GK Dziugaite, DM Roy arXiv preprint arXiv:1802.09583, 2018	75	2018
Learning annotated hierarchies from relational data DM Roy, C Kemp, V Mansinghka, J B Tenenbaum Carnegie Mellon University, 2007	73	2007
Information-theoretic generalization bounds for SGLD via data-dependent estimates J Negrea, M Haghifam, GK Dziugaite, A Khisti, DM Roy arXiv preprint arXiv:1911.02151, 2019	60	2019

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