# Difference between revisions of "f11Stat946presentation"

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− | |Nov 15 (Presentation 1)|| Azin Ashkan || A Dynamic Bayesian Network Click Model for Web Search Ranking || [http:// | + | |Nov 15 (Presentation 1)|| Azin Ashkan || A Dynamic Bayesian Network Click Model for Web Search Ranking || [http://olivier.chapelle.cc/pub/DBN_www2009.pdf]||[[A Dynamic Bayesian Network Click Model for Web Search Ranking|Summary]] |

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− | |Nov 15 (Presentation 2)|| Keyvan Golestan || Decentralised Data Fusion: A Graphical Model Approach || [http://isif.org/fusion/proceedings/fusion09CD/data/papers/0280.pdf] | + | |Nov 15 (Presentation 2)|| Keyvan Golestan || Decentralised Data Fusion: A Graphical Model Approach || [http://isif.org/fusion/proceedings/fusion09CD/data/papers/0280.pdf]||[[Decentralised Data Fusion: A Graphical Model Approach (Summary)|Summary]] |

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− | |Nov 17 (Presentation 1)|| Venkata Manem || Quantifying cancer progression with conjunctive Bayesian networks.|| [http://bioinformatics.oxfordjournals.org/content/25/21/2809.full.pdf] | + | |Nov 17 (Presentation 1)|| Venkata Manem || Quantifying cancer progression with conjunctive Bayesian networks.|| [http://bioinformatics.oxfordjournals.org/content/25/21/2809.full.pdf] || [[Quantifying cancer progression with conjunctive Bayesian networks.|Summary]] |

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− | |Nov 17 (Presentation 2)|| Mohammad Rostami ||Compressed Sensing Reconstruction via Belief Propagation ||[http://dsp.rice.edu/sites/dsp.rice.edu/files/cs/csbpTR07142006.pdf] | + | |Nov 17 (Presentation 2)|| Mohammad Rostami ||Compressed Sensing Reconstruction via Belief Propagation ||[http://dsp.rice.edu/sites/dsp.rice.edu/files/cs/csbpTR07142006.pdf]|| [[Compressed Sensing Reconstruction via Belief Propagation|Summary]] |

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− | |Nov 22 (Presentation 1)|| Mazen A. Melibari || | + | |Nov 22 (Presentation 1)|| Mazen A. Melibari ||An HDP-HMM for Systems with State Persistence|| [http://www.cs.brown.edu/~sudderth/papers/icml08.pdf] |

+ | || [[An HDP-HMM for Systems with State Persistence|Summary]] | ||

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− | |Nov 22 (Presentation 2)||Tameem Adel|| Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Sub-cellular Location Patterns || [http://jmlr.csail.mit.edu/papers/volume9/chen08a/chen08a.pdf] | + | |Nov 22 (Presentation 2)||Tameem Adel|| Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Sub-cellular Location Patterns || [http://jmlr.csail.mit.edu/papers/volume9/chen08a/chen08a.pdf] || [[Graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns|Summary]] |

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− | |Nov 24 (Presentation 1)|| Pouria Fewzee || Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis || [http://mi.eng.cam.ac.uk/~ky219/papers/yu-is10.pdf] | + | |Nov 24 (Presentation 1)|| Pouria Fewzee || Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis || [http://mi.eng.cam.ac.uk/~ky219/papers/yu-is10.pdf] || [[Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis|Summary]] |

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− | |Nov 24 (Presentation 2)|| Ali-Akbar Samadani || || | + | |Nov 24 (Presentation 2)|| Ali-Akbar Samadani ||Incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains || [http://ijr.sagepub.com/content/27/7/761.abstract]||[[Incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)|Summary]] |

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− | |Nov 29 (Presentation 1)||Hojatollah Yeganeh || | + | |Nov 29 (Presentation 1)||Hojatollah Yeganeh ||Markov Random Fields for Super-Resolution ||[http://www.merl.com/reports/docs/TR2000-08.pdf]||[[Markov Random Fields for Super-Resolution|Summary]] |

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− | |Nov 29 (Presentation 2)||Areej Alhothali || Video-based face recognition using adaptive hidden markov models||[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1211373] | + | |Nov 29 (Presentation 2)||Areej Alhothali || Video-based face recognition using adaptive hidden markov models||[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1211373]||[[Video-based face recognition using Adaptive HMM|Summary]] |

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## Latest revision as of 09:45, 30 August 2017

Sign up for your presentation in the following table. Chose a date between Nov 15 and Dec 1 (inclusive). You just need to sign up your name at the moment. When you chose the paper that you would like to present, add its title and a link to the paper.

Date | Speaker | Title | Link | Summary |

Nov 15 (Presentation 1) | Azin Ashkan | A Dynamic Bayesian Network Click Model for Web Search Ranking | [1] | Summary |

Nov 15 (Presentation 2) | Keyvan Golestan | Decentralised Data Fusion: A Graphical Model Approach | [2] | Summary |

Nov 17 (Presentation 1) | Venkata Manem | Quantifying cancer progression with conjunctive Bayesian networks. | [3] | Summary |

Nov 17 (Presentation 2) | Mohammad Rostami | Compressed Sensing Reconstruction via Belief Propagation | [4] | Summary |

Nov 22 (Presentation 1) | Mazen A. Melibari | An HDP-HMM for Systems with State Persistence | [5] | Summary |

Nov 22 (Presentation 2) | Tameem Adel | Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Sub-cellular Location Patterns | [6] | Summary |

Nov 24 (Presentation 1) | Pouria Fewzee | Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis | [7] | Summary |

Nov 24 (Presentation 2) | Ali-Akbar Samadani | Incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains | [8] | Summary |

Nov 29 (Presentation 1) | Hojatollah Yeganeh | Markov Random Fields for Super-Resolution | [9] | Summary |

Nov 29 (Presentation 2) | Areej Alhothali | Video-based face recognition using adaptive hidden markov models | [10] | Summary |