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danroy.org

Daniel Roy

Foundations of machine learning and statistics; Bayesian nonparametric statistics; computable probability theory; probabilistic programming languages.

http://www.danroy.org/

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Daniel Roy | danroy.org Reviews
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Foundations of machine learning and statistics; Bayesian nonparametric statistics; computable probability theory; probabilistic programming languages.
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1 Dan Roy
2 droy
3 Daniel M. Roy
4 mondrian process
5 Church
6 probabilistic programming
7 nonstandard analysis
8 graphex
9 computable probability theory
10
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assistant professor,cross appointment,university of toronto,founding faculty,vector institute,jump to teaching,research articles,news,probabilistic programming,curriculum vitæ,joining my group,undergraduates at toronto,prospective graduate students,group
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Daniel Roy | danroy.org Reviews

https://danroy.org

Foundations of machine learning and statistics; Bayesian nonparametric statistics; computable probability theory; probabilistic programming languages.

INTERNAL PAGES

danroy.org danroy.org
1

Root - Marginalia

http://danroy.org/marginalia

Welcome to the root page of marginalia. The purpose of this website is to serve as a repository for various marginalia, including errata, examples, notes, citations, further details, etc. Edits are restricted to those with accounts, which are handled by administrators for each project. In addition, this wiki hosts several articles on mathematical notation. Mathematical notation and conventions. Notation for conditional distributions borrowed from statistics. Book and manuscript marginalia. This page was ...

2

STAD68 -- 2015 -- Daniel Roy

http://danroy.org/teaching/2015/STAD68

Advanced Machine Learning and Data Mining. Statistical aspects of supervised learning: regression, regularization methods, parametric and nonparametric classification methods, including Gaussian processes for regression and support vector machines for classification, model averaging, model selection, and mixture models for unsupervised learning. Some advanced methods will include Bayesian networks and graphical models. Time, Location, Etc. Winter 2015, Mondays 7- 10pm from Jan. 5.

3

STAC63 -- 2015 -- Daniel Roy

http://danroy.org/teaching/2015/STAC63

This course continues the development of probability theory begun in STAB52. Probability models covered include branching processes, birth and death processes, renewal processes, Poisson processes, queuing theory, random walks and Brownian motion. Time, Location, Etc. Fall 2015, Mondays 7- 10pm from Sept. 14. Introduction to Probability Models, 11th edition. The 11th edition is available as an e-book (PDF) from the UofT library via the link above. Birth and death processes.

4

Curriculum Vitae, Daniel Roy

http://danroy.org/cv

Last updated: Fall 2014. Daniel M. Roy aka dan roy / daniel m. roy. Dept of Statistical Sciences. Sidney Smith, Office SS6026. 100 St. George St. T: 1 (416) 946 7587. F: 1 (416) 978 5133. Dept of Computer and Mathematical Sciences. Univ of Toronto Scarborough. IC Building, Office IC462. T: 1 (416) 287 5653. F: 1 (416) 287 7409. Droy utstat toronto edu. Daniel.roy utoronto ca (StG), daniel.roy utsc utoronto ca (UTSC). Assistant Professor (2014–. Department of Statistical Sciences, University of Toronto.

5

STA4513 -- 2014 -- Daniel Roy

http://danroy.org/teaching/2014/STA4513

Statistical Models of Networks, Graphs, and other Relational Structures. This course is a survey of topics on the statistical analysis of network, graph, and relational data, with an emphasis on network modeling and random graphs. In particular, the role of probabilistic symmetries- -including exchangeability and stationarity- -will be our primary concern, at least in the second half. Mathematical maturity and some background in linear algebra, analysis, measure theory, and probability theory recommended.

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utstat.toronto.edu utstat.toronto.edu

Haosui Duanmu

http://www.utstat.toronto.edu/~haosui

PhD candidate, Department of Statistical Sciences, University of Toronto. I employ techniques from nonstandard analysis to shed new light on foundational structures in probability theory and statistics. I am advised by Jeffrey Rosenthal. Stats, Math) and William Weiss. Math), and also work closely with Daniel Roy. Many of my friends call me Kevin. Productively Lindelöf and indestructibly Lindelöf spaces. Haosui Duanmu, Franklin D. Tall, and Lyubomyr Zdomskyy. Topology and its Applications.

gatsby.ucl.ac.uk gatsby.ucl.ac.uk

Balaji Lakshminarayanan

http://www.gatsby.ucl.ac.uk/~balaji

I am a research scientist at Google DeepMind. I am interested in Machine Learning. And its cool applications. E-mail: balaji (at) gatsby (dot) ucl.ac.uk. Before joining DeepMind, I was a PhD student at Gatsby Unit. Working with Yee Whye Teh. Between 2008-10, I was a Masters student at Oregon State University. Working with Raviv Raich. As part of the Bioacoustics research group. During my undergrad, I was part of the Integrated Systems laboratory. Decision trees and forests: a probabilistic perspective.

learning.cs.toronto.edu learning.cs.toronto.edu

UofT Machine Learning | People

http://learning.cs.toronto.edu/people

Eddie K.H. Ng. Matthew J. Beal. Miguel A. Carreira-Perpinan.

cocosci.mit.edu cocosci.mit.edu

MIT Computational Cognitive Science Group - People

http://cocosci.mit.edu/people

MIT Computational Cognitive Science Group. Department of Brain and Cognitive Sciences, MIT. In my research, I develop mathematical models of the way children learn language and the way adults generalize linguistic rules to create new words and sentences. My research draws on experimental methods from psychology, formal modeling techniques from natural language processing, theoretical tools from linguistics, and problems from all three. I am interested in these basic questions, working on modeling both in...

probabilistic-programming.org probabilistic-programming.org

NIPS*2008 Workshop - Probabilistic Programming

http://www.probabilistic-programming.org/wiki/NIPS*2008_Workshop

Funded in part by. Universal Languages and Inference; Systems; and Applications. December 13-14th, 2008. SATURDAY, DEC. 13, 2008. SUNDAY, DEC. 14, 2008. If you want to join our workshop mailing list and receive important announcements directly, please visit the following link and sign up: http:/ lists.csail.mit.edu/mailman/listinfo/probabilistic-programming. OCT 21 2008 Submissions Due. OCT 28 2008 Notifications Sent. DEC 13 2008 Workshop, first day. DEC 14 2008 Workshop, second day ( confirmed. J Lloyd,...

probabilistic-programming.org probabilistic-programming.org

NIPS*2012 Workshop - Probabilistic Programming

http://www.probabilistic-programming.org/wiki/NIPS*2012_Workshop

Funded in part by. December 7-8th, 2012. Lake Tahoe, Nevada. DAY 1 - FRIDAY DECEMBER 7. DAY 2 - SATURDAY DECEMBER 8. Oct 15, 2012. Nov 01, 2012. Notifications have been sent out. If you have not heard from us, contact us immediately. NIPS Early Reg. deadline. Nov 9, 2012. Dec 7–8, 2012 (two days). DAY 1 - FRIDAY DECEMBER 7. Invited talk: Modeling human common sense with probabilistic programs. Contributed talk: Automated variational inference in probabilistic programming. David Wingate and Theo Weber.

probabilistic-programming.org probabilistic-programming.org

NIPS*2014 Workshop - Probabilistic Programming

http://probabilistic-programming.org/wiki/NIPS*2014_Workshop

Funded in part by. 3rd NIPS Workshop on PROBABILISTIC PROGRAMMING. Saturday, December 13, 2014. Montreal, Quebec, Canada. The 3rd NIPS Workshop on Probabilistic Programming will survey recent progress, including results from the ongoing DARPA PPAML program. A key theme will be articulating formal connections between probabilistic programming and other fields central to the NIPS community. We have created a Google groups mailing list called 3rd-nips-workshop-on-probabilistic-programming. Fully Automatic V...

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Dan Roy's Portal Site

Dan Roy's Personal Websites.

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Daniel Roy

Dan Roy aka daniel roy, daniel m roy, droy. Department of Statistical Sciences. Department of Computer Science. Department of Computer and Mathematical Sciences. University of Toronto Scarborough. I welcome these emails, but they should include a c.v., lists of relevant course work, and a transcript. The subject line should contain the word "consideration" to indicate these instructions have been read. Students seeking short-term research opportunities:. And should include the word "consideration" in the...

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