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== General Info ==
== General Info ==
* Instructor: prof. [http://www.lems.brown.edu/~rfabbri Ricardo Fabbri], Ph.D. Brown University
* Instructor: prof. [http://www.lems.brown.edu/~rfabbri Ricardo Fabbri], Ph.D. Brown University
* Meeting times: Tues 12:30pm-2pm, Thursdays 2:20pm - 4pm
* Meeting times: Tues 6pm-7:40pm, Weds 5pm - 6:40pm
* Evaluation criteria: 1 quizz at the end of the term (60%), plus practical projects (40%).
* Evaluation criteria:  
* Forum for file exchange and discussion: [http://uerj.tk uerj.tk]
* Forum for file exchange and discussion: [http://uerj.tk uerj.tk]


=== Pre-requisites ===
=== Pre-requisites ===
* Linux - intermediate to advanced (will be reviewed as needed) - read [[Literatura recomendada pela equipe|Recommended Reading]]
* Undergraduate-level mathematics and probability (will review as needed)
* C/C++ - intermediate to advanced (will be reviewed) - read [[Literatura recomendada pela equipe|Recommended Reading]]
** [[Configuring Ubuntu for Programming]]
* Basic understanding of computer architecture - read  "Computer Systems: A Programmer's perspective" listed at [[Literatura recomendada pela equipe|Recommended Reading]].


== Approximate Content ==
== Approximate Content ==


The course focuses on software techniques for parallel computing.  We are aiming at a comprehensive treatment on different types of practical parallel programming techniques
* process-oriented parallel programming
* thread programming/thread safety
* single-core vector instructions
* multi-processor and multi-core programming
* mapreduce/hadoop
* MPI
* Cuda/OpenCL
* Dataflow techniques
Each of the above techniques would merit a course of their own, as done in many of the best universities. Therefore we aim at attaining a practical familiarity with each, in the first half of the course, and we will specialize in the later part of the course as to help the students' graduate research.


== Main Resources ==
== Main Resources ==

Edição das 01h30min de 9 de abril de 2013

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 IPRJ/UERJ. It is generally useful for computer scientists, statisticians, and applied mathematicians.

General Info

  • Instructor: prof. Ricardo Fabbri, Ph.D. Brown University
  • Meeting times: Tues 6pm-7:40pm, Weds 5pm - 6:40pm
  • Evaluation criteria:
  • Forum for file exchange and discussion: uerj.tk

Pre-requisites

  • Undergraduate-level mathematics and probability (will review as needed)

Approximate Content

Main Resources

Textbooks

Lectures

Partial listing & Tentative Outline

  1. Overview of pattern theory and classic pattern recognition

Homework

Keywords

Portuguese: Teoria dos Padrões, Reconhecimento de Padrões, Visão Computacional, Inteligência Artificial, Formação de Padrões