Sam T. Roweis

Affiliations: 
2001-2007 University of Toronto, Toronto, ON, Canada 
 2007-2009 Google, Inc., Mountain View, CA, United States 
 2009-2010 Computer Science New York University, New York, NY, United States 
Area:
Machine learning
Website:
http://www.cs.nyu.edu/~roweis/
Google:
"Sam T. Roweis"
Bio:

(1972 - 2010)
https://aas.org/obituaries/sam-roweis-1972-2010
http://samroweis1972-2010.blogspot.nl/
Roweis, Sam T. Data driven production models for speech processing. Dissertation (Ph.D.), California Institute of Technology (1999).

Mean distance: 13.51 (cluster 17)
 
SNBCP
Cross-listing: Computer Science Tree

Parents

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John J. Hopfield grad student 1999 Caltech
 (Data driven production models for speech processing.)
Zoubin Ghahramani post-doc UCL
Geoffrey E. Hinton post-doc UCL

Children

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Graham Taylor grad student (Computer Science Tree)
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Publications

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Marlin BM, Zemel RS, Roweis ST, et al. (2011) Recommender systems: Missing data and statistical model estimation Ijcai International Joint Conference On Artificial Intelligence. 2686-2691
Bovy J, Hogg DW, Roweis ST. (2011) Extreme deconvolution: Inferring complete distribution functions from noisy, heterogeneous and incomplete observations Annals of Applied Statistics. 5: 1657-1677
Taylor GW, Hinton GE, Roweis ST. (2011) Two distributed-state models for generating high-dimensional time series Journal of Machine Learning Research. 12: 1025-1068
Lang D, Hogg DW, Mierle K, et al. (2010) Astrometry.net: Blind astrometric calibration of arbitrary astronomical images Astronomical Journal. 139: 1782-1800
Bovy J, Hogg DW, Roweis ST. (2009) The velocity distribution of nearby stars from hipparcos data. I. the significance of the moving groups Astrophysical Journal. 700: 1794-1819
Platt J, Koller D, Singer Y, et al. (2009) Preface Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference. iii
Teo CH, Globerson A, Roweis S, et al. (2009) Convex learning with invariances Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference
Meeds EW, Ross DA, Zemel RS, et al. (2008) Learning stick-figure models using nonparametric Bayesian priors over trees 26th Ieee Conference On Computer Vision and Pattern Recognition, Cvpr
Barron JT, Hogg DW, Lang D, et al. (2008) Blind date: Using proper motions to determine the ages of historical images Astronomical Journal. 136: 1490-1501
Barron JT, Stumm C, Hogg DW, et al. (2008) Cleaning the USNO-B catalog through automatic detection of optical artifacts Astronomical Journal. 135: 414-422
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