Talk:Algorithms Seminar/Fall11

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5) Gradient Descent / Hill Climbing:  
5) Gradient Descent / Hill Climbing:  
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[http://webdocs.cs.ualberta.ca/~sutton/book/8/node3.html 1]
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[http://webdocs.cs.ualberta.ca/~sutton/book/8/node3.html 1],
[http://www.ri.cmu.edu/pub_files/pub1/baird_leemon_1999_1/baird_leemon_1999_1.pdf 2]
[http://www.ri.cmu.edu/pub_files/pub1/baird_leemon_1999_1/baird_leemon_1999_1.pdf 2]
6) Alternating Optimization, EM like methods:  
6) Alternating Optimization, EM like methods:  
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[http://geomblog.blogspot.com/2008/01/important-heuristics-alternating.html 1]
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[http://geomblog.blogspot.com/2008/01/important-heuristics-alternating.html 1],
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[http://www.springerlink.com/content/c21tfr6cxmjbmq3r/ 2]
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[http://www.springerlink.com/content/c21tfr6cxmjbmq3r/ 2],
[http://dl.acm.org/citation.cfm?id=964886 3]
[http://dl.acm.org/citation.cfm?id=964886 3]
7) Swarm Intelligence based methods:  
7) Swarm Intelligence based methods:  
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[http://www.springerlink.com/content/q528q1743224q233/ 1]
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[http://www.springerlink.com/content/q528q1743224q233/ 1],
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[www.idsia.ch/~luca/aco2004.pdf Ant colony optimization]
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[www.idsia.ch/~luca/aco2004.pdf Ant colony optimization],
[http://www.inderscience.com/filter.php?aid=22775 Intelligent Water Drops]
[http://www.inderscience.com/filter.php?aid=22775 Intelligent Water Drops]
8) Metropolis-Hastings algorithm:  
8) Metropolis-Hastings algorithm:  
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[http://elsa.berkeley.edu/reprints/misc/understanding.pdf
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[http://elsa.berkeley.edu/reprints/misc/understanding.pdf 1],
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[http://fedc.wiwi.hu-berlin.de/xplore/ebooks/html/csa/node27.html
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[http://fedc.wiwi.hu-berlin.de/xplore/ebooks/html/csa/node27.html 2]
9) Nelder-Mead Method:  
9) Nelder-Mead Method:  
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[http://math.fullerton.edu/mathews/n2003/neldermead/NelderMeadProof.pdf
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[http://math.fullerton.edu/mathews/n2003/neldermead/NelderMeadProof.pdf 1]
11) Monkey Search:  
11) Monkey Search:  
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[www.ise.ufl.edu/cao/Book_DMSAOB/009mucherino.pdf
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[http://www.ise.ufl.edu/cao/Book_DMSAOB/009mucherino.pdf 1]
12) Firefly Algorithm:  
12) Firefly Algorithm:  
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[http://groups.csail.mit.edu/mac/projects/amorphous/HC11/fcresear.html
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[http://groups.csail.mit.edu/mac/projects/amorphous/HC11/fcresear.html 1],
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[http://bluescarni.info/documents/lukasik_firefly.pdf
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[http://bluescarni.info/documents/lukasik_firefly.pdf 2],
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[http://arxiv.org/abs/1003.1464
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[http://arxiv.org/abs/1003.1464 3]
13) No free lunch in search and optimization:  
13) No free lunch in search and optimization:  
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[http://ti.arc.nasa.gov/m/profile/dhw/papers/78.pdf
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[http://ti.arc.nasa.gov/m/profile/dhw/papers/78.pdf 1]
14) Heuristics for NP-hard problems:  
14) Heuristics for NP-hard problems:  
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[www.cs.ubc.ca/~hutter/previous-earg/EmpAlgReadingGroup/Sau02.pdf Heuristic SAT]
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[http://www.cs.ubc.ca/~hutter/previous-earg/EmpAlgReadingGroup/Sau02.pdf Heuristic SAT],
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[www.academic.marist.edu/~jzbv/algorithms/approximatetspalgorithms.pdf Heuristic TSP]
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[http://www.academic.marist.edu/~jzbv/algorithms/approximatetspalgorithms.pdf Heuristic TSP],
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[http://www-e.uni-magdeburg.de/mertens/TSP/ TSP Animation]
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[http://www-e.uni-magdeburg.de/mertens/TSP/ TSP Animation],
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[http://www.cs.amherst.edu/~ccm/cs34/papers/tabuveh2661622.pdf TABUROUTE]
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[http://www.cs.amherst.edu/~ccm/cs34/papers/tabuveh2661622.pdf TABUROUTE],
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[http://dl.acm.org/citation.cfm?id=1224164 Heuristic Vehicle Routing Problem]
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[http://dl.acm.org/citation.cfm?id=1224164 Heuristic Vehicle Routing Problem],
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[http://www.iro.umontreal.ca/~gendron/PLU6000/chap5ca99b.ps Vehicle Routing 2]
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[http://www.iro.umontreal.ca/~gendron/PLU6000/chap5ca99b.ps Vehicle Routing 2],
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[http://www.diku.dk/hjemmesider/ansatte/sropke/Papers/PHDThesis.pdf Routing-thesis]
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[http://www.diku.dk/hjemmesider/ansatte/sropke/Papers/PHDThesis.pdf Routing-thesis],
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[http://home.dei.polimi.it/malucell/papers/stellac.pdf Heuristic Set Cover]
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[http://home.dei.polimi.it/malucell/papers/stellac.pdf Heuristic Set Cover],
[http://dl.acm.org/citation.cfm?id=89230 Heuristic Task Scheduling]
[http://dl.acm.org/citation.cfm?id=89230 Heuristic Task Scheduling]

Revision as of 18:19, 18 August 2011

Possible Topics:

1) Cuckoo Search: 1

2) Simulated Annealing: 1

3) SVM: 1

4) Evolutionary Algorithms: 1

5) Gradient Descent / Hill Climbing: 1, 2

6) Alternating Optimization, EM like methods: 1, 2, 3

7) Swarm Intelligence based methods: 1, [www.idsia.ch/~luca/aco2004.pdf Ant colony optimization], Intelligent Water Drops

8) Metropolis-Hastings algorithm: 1, 2

9) Nelder-Mead Method: 1

11) Monkey Search: 1

12) Firefly Algorithm: 1, 2, 3

13) No free lunch in search and optimization: 1

14) Heuristics for NP-hard problems: Heuristic SAT, Heuristic TSP, TSP Animation, TABUROUTE, Heuristic Vehicle Routing Problem, Vehicle Routing 2, Routing-thesis, Heuristic Set Cover, Heuristic Task Scheduling


Related areas:

Metaheuristics: Search within a search space of problem solutions. Hyper-heuristics: Search within a search space of heuristics.


Talks:

Effective Heuristics for NP-Hard Problems, Richard Karp


Books:

J Pearl, Heuristics: intelligent search strategies for computer problem solving. CR Reeves, Modern Heuristic Techniques for Combinatorial Problems. Eric Bonabeau, Marco Dorigo, Guy Theraulaz, Swarm intelligence: from natural to artificial systems. Yang, Nature-Inspired Metaheuristic Algorithms

Other Links: Heuristic Search: http://www.cs.cf.ac.uk/Dave/AI2/node23.html Combinatorial Optimization: http://www.ida.liu.se/~zebpe/heuristic/ NP Hard problems and heuristics: http://www.cs.uky.edu/~lewis/cs-heuristic/text/contents.html Analysis of heuristics: Thesis: Eran Ofek, Rigorous Analysis of Heuristics for NP-hard Problems

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