Pattern Theory and Applications - Histórico de revisão

V1z: home page update

2020-08-18T17:47:09Z

home page update

← Edição anterior		Edição das 14h47min de 18 de agosto de 2020
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	== General Info ==		== General Info ==
	* Instructors: prof. Francisco Duarte Moura Neto, Ph.D. Berkeley, and prof. [http://~~www~~.~~lems~~.~~brown.edu/~rfabbri~~ Ricardo Fabbri], Ph.D. Brown University		* Instructors: prof. Francisco Duarte Moura Neto, Ph.D. Berkeley, and prof. [http://rfabbri.github.io Ricardo Fabbri], Ph.D. Brown University
	* Meeting times: Thursdays 3:10pm - 6:45pm, Room 210.		* Meeting times: Thursdays 3:10pm - 6:45pm, Room 210.
	* Forum for file exchange and discussion: [http://uerj.tk uerj.tk]		* Forum for file exchange and discussion: [http://uerj.tk uerj.tk]

V1z: updated to 2015

2015-03-26T10:43:05Z

updated to 2015

← Edição anterior		Edição das 07h43min de 26 de março de 2015
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	This is the main page of a graduate-level course in pattern theory, machine learning, pattern formation, pattern recognition and computer vision being taught in ~~2014~~/2 at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ. It is generally useful for computer scientists, statisticians, and applied mathematicians wishing to automatically model and analyze phenomena from sets of images and other signals. Think of this course as a special 'flavor' of artificial intelligence which has been largely developed at one of the instructor's ''alma mater'', Brown University, through researchers such as fields medalist David Mumford and Ulf Grenader.		This is the main page of a graduate-level course in pattern theory, machine learning, pattern formation, pattern recognition and computer vision being taught in 2015/2 at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ. It is generally useful for computer scientists, statisticians, and applied mathematicians wishing to automatically model and analyze phenomena from sets of images and other signals. Think of this course as a special 'flavor' of artificial intelligence which has been largely developed at one of the instructor's ''alma mater'', Brown University, through researchers such as fields medalist David Mumford and Ulf Grenader.
	[[Image:Fruitflyembryo.jpg\|right\|300px]]		[[Image:Fruitflyembryo.jpg\|right\|300px]]

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	== General Info ==		== General Info ==
	* Instructors: prof. Francisco Duarte Moura Neto, Ph.D. Berkeley, and prof. [http://www.lems.brown.edu/~rfabbri Ricardo Fabbri], Ph.D. Brown University		* Instructors: prof. Francisco Duarte Moura Neto, Ph.D. Berkeley, and prof. [http://www.lems.brown.edu/~rfabbri Ricardo Fabbri], Ph.D. Brown University
	* Meeting times: Thursdays 9:~~40am~~ - 1:~~20pm~~, Room 210.		* Meeting times: Thursdays 3:10pm - 6:45pm, Room 210.
	* Forum for file exchange and discussion: [http://uerj.tk uerj.tk]		* Forum for file exchange and discussion: [http://uerj.tk uerj.tk]

V1z: link para 2014

2015-03-26T10:37:34Z

link para 2014

← Edição anterior		Edição das 07h37min de 26 de março de 2015
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	* Link to the '''[[PT2013\|2013 ~~course page~~]]'''		* Link to the course pages for previous years: '''[[PT2013\|2013]],[[PT2014\|2014]]'''

	== General Info ==		== General Info ==

V1z: /* Misc. Notes */ mauro resumo

2014-09-26T00:14:36Z

Misc. Notes: mauro resumo

← Edição anterior		Edição das 21h14min de 25 de setembro de 2014
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	== Misc. Notes ==		== Misc. Notes ==
	~~The~~		* Slides by Mauro de Amorim summarizing part I of the course [https://pt.sharelatex.com/project/54245152694cc3585873f383]

	== Homework ==		== Homework ==

V1z: /* Course Format */

2014-09-15T21:11:52Z

Course Format

← Edição anterior		Edição das 18h11min de 15 de setembro de 2014
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	** Readings must be summarized with '''personal opinions and reflexions''' and a summary must be typed and handed in		** Readings must be summarized with '''personal opinions and reflexions''' and a summary must be typed and handed in
	** Discussion and coding in class will be graded as "class participation"		** Discussion and coding in class will be graded as "class participation"
	** '''Bring your laptops ~~on Wednesdays~~!'''		** '''Bring your laptops!'''

	=== Pre-requisites ===		=== Pre-requisites ===

V1z: /* General Info */

2014-09-15T21:11:15Z

General Info

← Edição anterior		Edição das 18h11min de 15 de setembro de 2014
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	== General Info ==		== General Info ==
	* Instructors: prof. Francisco Duarte Moura Neto, Ph.D. Berkeley, and prof. [http://www.lems.brown.edu/~rfabbri Ricardo Fabbri], Ph.D. Brown University		* Instructors: prof. Francisco Duarte Moura Neto, Ph.D. Berkeley, and prof. [http://www.lems.brown.edu/~rfabbri Ricardo Fabbri], Ph.D. Brown University
	* Meeting times: ~~Tues 6pm~~-7:~~40pm~~, ~~Weds 5pm - 6:40pm~~		* Meeting times: Thursdays 9:40am - 1:20pm, Room 210.
	* Forum for file exchange and discussion: [http://uerj.tk uerj.tk]		* Forum for file exchange and discussion: [http://uerj.tk uerj.tk]

V1z: link to 2013

2014-09-15T21:08:00Z

link to 2013

← Edição anterior		Edição das 18h08min de 15 de setembro de 2014
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	This is the main page of a graduate-level course in pattern theory, machine learning, pattern formation, pattern recognition and computer vision being taught in ~~2013~~/1 at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ. It is generally useful for computer scientists, statisticians, and applied mathematicians wishing to automatically model and analyze phenomena from sets of images and other signals. Think of this course as a special 'flavor' of artificial intelligence which has been largely developed at one of the instructor's ''alma mater'', Brown University, through researchers such as fields medalist David Mumford and Ulf Grenader.		This is the main page of a graduate-level course in pattern theory, machine learning, pattern formation, pattern recognition and computer vision being taught in 2014/2 at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ. It is generally useful for computer scientists, statisticians, and applied mathematicians wishing to automatically model and analyze phenomena from sets of images and other signals. Think of this course as a special 'flavor' of artificial intelligence which has been largely developed at one of the instructor's ''alma mater'', Brown University, through researchers such as fields medalist David Mumford and Ulf Grenader.
	[[Image:Fruitflyembryo.jpg\|right\|300px]]		[[Image:Fruitflyembryo.jpg\|right\|300px]]

			* Link to the '''[[PT2013\|2013 course page]]'''

	== General Info ==		== General Info ==

V1z: /* Main Resources */ aula de pagerank

2013-07-03T17:43:15Z

Main Resources: aula de pagerank

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	# Word Boundaries Machine Translation		# Word Boundaries Machine Translation
	# Practical programming of Ch 1 - DNA Sequence statistics, p. 56 ex 6		# Practical programming of Ch 1 - DNA Sequence statistics, p. 56 ex 6
			# [http://wiki.nosdigitais.teia.org.br/Imagem:Aula-pagerank.pdf Extra lecture on Markov Chains - Google PageRank and markov chains for organizing large networks and machine learning]
	'''Part II of Course: lets jump to Chapter 5: Flexible Templates'''		'''Part II of Course: lets jump to Chapter 5: Flexible Templates'''
	# Overview of manifolds, differential geometry of surfaces and higher dimensions		# Overview of manifolds, differential geometry of surfaces and higher dimensions

V1z: /* Main Resources */

2013-07-02T01:47:32Z

Main Resources

← Edição anterior		Edição das 22h47min de 1 de julho de 2013
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	# Overview of manifolds, differential geometry of surfaces and higher dimensions		# Overview of manifolds, differential geometry of surfaces and higher dimensions
	# Bird's eye view of Mumford's research on diffeomorphisms and infinite dimensional differential goemetry		# Bird's eye view of Mumford's research on diffeomorphisms and infinite dimensional differential goemetry
			## See Mumford's presentations (on the right)
			## Infinite dimensional nonlinear manifolds and their applications to shape were already predicted by Riemann: ''"There are however manifolds in which the fixing of position requires not a finite number but either an infinite series or a continuous manifold of determinations of quantity. Such manifolds are constituted for example by ... the possible shapes of a figure in space, etc."''

			== Misc. Notes ==
			The

	== Homework ==		== Homework ==

V1z: /* Main Resources */

2013-07-02T01:33:07Z

Main Resources

← Edição anterior		Edição das 22h33min de 1 de julho de 2013
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	==== Partial listing & Tentative Outline ====		==== Partial listing & Tentative Outline ====
			'''Part I Chapters 0 and 1 - pattern theory overview and intro to its basic methods through text processing'''
	# Overview of pattern theory and classic pattern recognition		# Overview of pattern theory and classic pattern recognition
	# The classical paradigm - machine learning, pattern recognition systems, clustering, recognition, and how it all fits together: the design of the ultimate AI system		# The classical paradigm - machine learning, pattern recognition systems, clustering, recognition, and how it all fits together: the design of the ultimate AI system
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	# Word Boundaries Machine Translation		# Word Boundaries Machine Translation
	# Practical programming of Ch 1 - DNA Sequence statistics, p. 56 ex 6		# Practical programming of Ch 1 - DNA Sequence statistics, p. 56 ex 6
	Part II of Course: lets jump to Chapter 5: Flexible Templates		'''Part II of Course: lets jump to Chapter 5: Flexible Templates'''
	# Overview of manifolds, differential geometry of surfaces and higher dimensions		# Overview of manifolds, differential geometry of surfaces and higher dimensions
	# Bird's eye view of Mumford's research on diffeomorphisms and infinite dimensional differential goemetry		# Bird's eye view of Mumford's research on diffeomorphisms and infinite dimensional differential goemetry