The Community for Technology Leaders
Green Image
TABLE OF CONTENTS
Issue No. 02 - Feb. (vol. 37)
ISSN: 0162-8828

Table of Contents (PDF)

pp. C1

Guest Editors’ Introduction to the Special Issue on Bayesian Nonparametrics (HTML)

Ryan P. Adams , Engineering and Applied Sciences, Harvard University, 33 Oxford St., Cambridge, MA
Emily B. Fox , Department of Statistics, Box 354322, Padelford Hall, Room B-305, University of Washington, Seattle, WA
Erik B. Sudderth , Department of Computer Science, 115 Waterman Street, Brown University, Box 1910, Providence, RI
Yee Whye Teh , Department of Statistics, University of Oxford, 1 South Parks Road, Oxford, OX1 3TG, United Kingdom
pp. 209-211

Are Gibbs-Type Priors the Most Natural Generalization of the Dirichlet Process? (Abstract)

Pierpaolo De Blasi , Department of Economics and Statistics, University of Torino, Torino, Italy
Stefano Favaro , Department of Economics and Statistics, University of Torino, Torino, Italy
Antonio Lijoi , , Collegio Carlo Alberto, Moncalieri, Italy
Ramses H. Mena , Department of Probability and Statistics, Universidad Nacional Autónoma de México, México, México
Igor Prunster , Department of Economics and Statistics, University of Torino, Torino, Italy
Matteo Ruggiero , Department of Economics and Statistics, University of Torino, Torino, Italy
pp. 212-229

Differential Topic Models (Abstract)

Changyou Chen , , Australian National University and National ICT, Australia
Wray Buntine , , Australian National University and National ICT, Australia
Nan Ding , , Google Inc., Los Angeles, CA
Lexing Xie , , Australian National University and National ICT, Australia
Lan Du , Department of Computing, Macquarie University, Sydney, Australia
pp. 230-242

The Supervised Hierarchical Dirichlet Process (Abstract)

Andrew M. Dai , , Google Inc., 1600 Amphitheatre Parkway, Mountain View, CA
Amos J. Storkey , Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, United Kingdom
pp. 243-255

Nested Hierarchical Dirichlet Processes (Abstract)

John Paisley , Department of Electrical Engineering, Columbia University, New York, NY
Chong Wang , , Voleon Capital Management, Berkeley, CA
David M. Blei , Department of Computer Science, Princeton University, Princeton, NJ
Michael I. Jordan , Departments of EECS and Statistics, UC Berkeley, Berkeley, CA
pp. 256-270

Pitman Yor Diffusion Trees for Bayesian Hierarchical Clustering (Abstract)

David A. Knowles , , Stanford University, Menlo Park, California
Zoubin Ghahramani , Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, England
pp. 271-289

Combinatorial Clustering and the Beta Negative Binomial Process (Abstract)

Tamara Broderick , Department of Statistics and the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA
Lester Mackey , Department of Statistics, Stanford University, Stanford, CA
John Paisley , Department of Electrical Engineering, Columbia University, New York, NY
Michael I. Jordan , Department of Statistics and the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA
pp. 290-306

Negative Binomial Process Count and Mixture Modeling (Abstract)

Mingyuan Zhou , Department of Information, Risk, and Operations Management, McCombs School of Business, University of Texas at Austin, Austin, TX, USA
Lawrence Carin , Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA
pp. 307-320

Latent IBP Compound Dirichlet Allocation (Abstract)

Cedric Archambeau , Amazon Berlin, , Berlin, Germany
Balaji Lakshminarayanan , Gatsby Computational Neuroscience Unit, CSML, University College London, London, U.K
Guillaume Bouchard , Xerox Research Centre Europe, Meylan, France
pp. 321-333

Distance Dependent Infinite Latent Feature Models (Abstract)

Samuel J. Gershman , Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA
Peter I. Frazier , School of Operations Research and Information Engineering, Cornell University, Ithaca, NY
David M. Blei , Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ
pp. 334-345

A Bayesian Nonparametric Approach to Image Super-Resolution (Abstract)

Gungor Polatkan , , Twitter Inc., San Francisco, CA
Mingyuan Zhou , Department of Statistics, University of Texas at Austin, Austin, TX
Lawrence Carin , Department of Electrical Engineering, Duke University, Durham, NC
David Blei , Department of Computer Science at Princeton University, Princeton, NJ
Ingrid Daubechies , Department of Mathematics, Duke University, Durham, NC
pp. 346-358

A Survey of Non-Exchangeable Priors for Bayesian Nonparametric Models (Abstract)

Nicholas J. Foti , Statistics Department, University of Washington, Seattle, WA, USA
Sinead A. Williamson , Department of InformationRisk and Operations Management, University of Texas at Austin, Austin, TX, USA
pp. 359-371

Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model (Abstract)

Zhiguang Xu , Department of Statistics, The Ohio State University, 404 Cockins Hall, 1958 Neil Ave., Columbus,
Steven MacEachern , Department of Statistics, The Ohio State University, 404 Cockins Hall, 1958 Neil Ave., Columbus,
Xinyi Xu , Department of Statistics, The Ohio State University, 404 Cockins Hall, 1958 Neil Ave., Columbus,
pp. 372-382

Fast Nonparametric Clustering of Structured Time-Series (Abstract)

James Hensman , Department of Computer Science and Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, South Yorkshire, United Kingdom
Magnus Rattray , Faculty of Life Sciences, University of Manchester, Manchester, Greater Manchester, United Kingdom
Neil D. Lawrence , Department of Computer Science and Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, South Yorkshire, United Kingdom
pp. 383-393

Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning (Abstract)

Finale Doshi-Velez , Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
David Pfau , Center for Theoretical Neuroscience, Columbia University, New York, NY, USA
Frank Wood , Department of Engineering, University of Oxford, Oxford, U.K.
Nicholas Roy , Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
pp. 394-407

Gaussian Processes for Data-Efficient Learning in Robotics and Control (HTML)

Marc Peter Deisenroth , Department of Computing, Imperial College London, 180 Queen’s Gate, London SW72AZ, United Kingdom
Dieter Fox , Department of Computer Science & Engineering, University of Washington, Box 352350, Seattle,
Carl Edward Rasmussen , Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB21PZ, United Kingdom
pp. 408-423

Scaling Multidimensional Inference for Structured Gaussian Processes (Abstract)

Elad Gilboa , Preston M. Green Department of Electrical and System Engineering, Washington University in St. Louis, 14049 Agusta Dr., Chesterfield,
Yunus Saatci , Department of Engineering, University of Cambridge, 47 Consort Avenue, CB2 9AE, Cambridge CB2 9AE, Cambridgeshire , United Kingdom
John P. Cunningham , Department of Statistics, Columbia University, Room 1026 SSW, MC 4690, 1255 Amsterdam Ave, New York,
pp. 424-436

Bayesian Models of Graphs, Arrays and Other Exchangeable Random Structures (Abstract)

Peter Orbanz , Department of Statistics, Columbia University, New York, NY
Daniel M. Roy , Department of Engineering, University of Cambridge, Cambridge CB2 3AP, United Kingdom
pp. 437-461

Bayesian Nonparametric Models for Multiway Data Analysis (Abstract)

Zenglin Xu , School of Computer Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
Feng Yan , , Facebook Inc., Menlo Park, CA, USA
Yuan Qi , Department of Computer Science and Department of Statistics, Purdue University, West Lafayette, USA
pp. 475-487

IEEE Computer Society (PDF)

pp. C4
85 ms
(Ver 3.3 (11022016))