# Differences

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 en:projects:details:epc09 [2009/06/05 18:57]masoud created en:projects:details:epc09 [2016/06/23 11:26] (current) 2010/09/21 08:44 masoud 2010/09/13 16:30 external edit2009/06/08 12:21 masoud 2009/06/05 23:05 cangiani 2009/06/05 18:58 masoud 2009/06/05 18:57 masoud created Next revision Previous revision 2010/09/21 08:44 masoud 2010/09/13 16:30 external edit2009/06/08 12:21 masoud 2009/06/05 23:05 cangiani 2009/06/05 18:58 masoud 2009/06/05 18:57 masoud created Line 1: Line 1: - ===== Expectation Propagation Decoding ===== + ---- dataentry project ---- - \\ + - + - **Expectation Propagation** is a method for approximate inference in Graphical Models. The aim of this project is to treat the tanner graph of LDPC code as a graphical model and to use EP technique for decoding. The proportion of theoretical and empirical (programming,​ simulation) work in this project is 40-60 percent. + - + - Requirement:​ + - * Good familiarity with basic probability theory + - * Good programming skills in Matlab and/or C/C++ + - What will you learn + - * LDPC codes + - * Learning and Inference in Graphical Models + - * Expectation Propagation + - * Fast implementation of approximate inference in graphical models + - Suggested Reading + - * [[http://​research.microsoft.com/​en-us/​um/​people/​minka/​papers/​ep/​|Thomas Minka'​s EP page]] + - * [[http://​videolectures.net/​abi07_walsh_cip/​|A Completed Information Projection Interpretation of Expectation Propagation]] + - + - ---- dataentry project ---- + title :  Expectation Propagation Decoding ​ title :  Expectation Propagation Decoding ​ contactname:​ Masoud Alipour contactname:​ Masoud Alipour - contactmail_mail:​ masoud ​[dot] alipour ​[at] epfl [dot] ch + contactmail_mail:​ masoud.alipour@epfl.ch contacttel: 021 6937529 contacttel: 021 6937529 contactroom:​ BC 150 contactroom:​ BC 150 type : master semester ​ type : master semester ​ - status ​: available + state : unavailable created_dt : 2009-06-03 created_dt : 2009-06-03 taken_dt :  ​ taken_dt :  ​ Line 33: Line 16: template:​datatemplates:​project template:​datatemplates:​project ---- ---- + + **Expectation Propagation** is a method for approximate inference in Graphical Models. The aim of this project is to treat the tanner graph of LDPC code as a graphical model and to use EP technique for decoding. The proportion of theoretical and empirical (programming,​ simulation) work in this project is 40-60 percent. + + Requirement:​ + * Good familiarity with basic probability theory + * Good programming skills in Matlab and/or C/C++ + What will you learn + * LDPC codes + * Learning and Inference in Graphical Models + * Expectation Propagation + * Fast implementation of approximate inference in graphical models + Suggested Readings and References ​ + * [[http://​research.microsoft.com/​en-us/​um/​people/​minka/​papers/​ep/​|Thomas Minka'​s EP page]] + * [[http://​videolectures.net/​abi07_walsh_cip/​|A Completed Information Projection Interpretation of Expectation Propagation]] +