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Workshop Details
OEDM: Workshop on Optimization Based Techniques for Emerging Data Mining
Organized by Yong Shi and Chris Ding
08:45 - 17:10
Room: Willumsen
http://www.feds.ac.cn/academic/Pages/academicShow.aspx?academicID=16
This workshop will present recent advances in optimization techniques for, especially new emerging, data mining problems, as well as the real-life applications among. One main goal of the workshop is to bring together the leading researchers who work on state-of-the-art algorithms on optimization based methods for modern data analysis, and also the practitioners who seek for novel applications.
| 08:45 - 09:10 | Anomalous Neighborhood Selection Satoshi Hara and Takashi WASHIO |
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08:45 - 09:10 | Anomalous Neighborhood Selection Satoshi Hara and Takashi WASHIO |
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08:45 - 09:10 | Anomalous Neighborhood Selection | event_type == 4) {?>Anomalous Neighborhood Selection | event_type == 5) {?>08:45 - 09:10 | Anomalous Neighborhood Selection Satoshi Hara and Takashi WASHIO |
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| 09:10 - 09:35 | The Performance of alternative Exchange Rate Regimes and Their Countries condition: Matching Analysis and Selection Model Building Haizhen Yang, Yunpeng Song, and Kun Guo |
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09:10 - 09:35 | The Performance of alternative Exchange Rate Regimes and Their Countries condition: Matching Analysis and Selection Model Building Haizhen Yang, Yunpeng Song, and Kun Guo |
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09:10 - 09:35 | The Performance of alternative Exchange Rate Regimes and Their Countries condition: Matching Analysis and Selection Model Building | event_type == 4) {?>The Performance of alternative Exchange Rate Regimes and Their Countries condition: Matching Analysis and Selection Model Building | event_type == 5) {?>09:10 - 09:35 | The Performance of alternative Exchange Rate Regimes and Their Countries condition: Matching Analysis and Selection Model Building Haizhen Yang, Yunpeng Song, and Kun Guo |
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| 09:35 - 10:00 | Employing Principal Hessian Direction for Building Hinging Hyperplane Models Anca Maria Ivanescu, Thivaharan Albin, Dirk Abel, and Thomas Seidl |
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09:35 - 10:00 | Employing Principal Hessian Direction for Building Hinging Hyperplane Models Anca Maria Ivanescu, Thivaharan Albin, Dirk Abel, and Thomas Seidl |
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09:35 - 10:00 | Employing Principal Hessian Direction for Building Hinging Hyperplane Models | event_type == 4) {?>Employing Principal Hessian Direction for Building Hinging Hyperplane Models | event_type == 5) {?>09:35 - 10:00 | Employing Principal Hessian Direction for Building Hinging Hyperplane Models Anca Maria Ivanescu, Thivaharan Albin, Dirk Abel, and Thomas Seidl |
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| 10:00 - 10:30 | Coffee Break |
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10:00 - 10:30 | Coffee Break |
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10:00 - 10:30 | Coffee Break | event_type == 4) {?>Coffee Break | event_type == 5) {?>10:00 - 10:30 | Coffee Break |
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| 10:30 - 10:55 | Nonlinear L-1 Support Vector Machines for Learning Using Privileged Information Lingfeng Niu, and Jianmin Wu |
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10:30 - 10:55 | Nonlinear L-1 Support Vector Machines for Learning Using Privileged Information Lingfeng Niu, and Jianmin Wu |
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10:30 - 10:55 | Nonlinear L-1 Support Vector Machines for Learning Using Privileged Information | event_type == 4) {?>Nonlinear L-1 Support Vector Machines for Learning Using Privileged Information | event_type == 5) {?>10:30 - 10:55 | Nonlinear L-1 Support Vector Machines for Learning Using Privileged Information Lingfeng Niu, and Jianmin Wu |
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| 10:55 - 11:20 | The Transfer Learning Based on Relationships between Attributes Jinwei Zhao, Boqin Feng, Guirong Yan, and Longlei Dong |
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10:55 - 11:20 | The Transfer Learning Based on Relationships between Attributes Jinwei Zhao, Boqin Feng, Guirong Yan, and Longlei Dong |
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10:55 - 11:20 | The Transfer Learning Based on Relationships between Attributes | event_type == 4) {?>The Transfer Learning Based on Relationships between Attributes | event_type == 5) {?>10:55 - 11:20 | The Transfer Learning Based on Relationships between Attributes Jinwei Zhao, Boqin Feng, Guirong Yan, and Longlei Dong |
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| 11:20 - 11:45 | Overlapping Clustering with Sparseness Constraints Haibing Lu, Yuan Hong, Nick Street, Fei Wang, and Hanghang Tong |
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11:20 - 11:45 | Overlapping Clustering with Sparseness Constraints Haibing Lu, Yuan Hong, Nick Street, Fei Wang, and Hanghang Tong |
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11:20 - 11:45 | Overlapping Clustering with Sparseness Constraints | event_type == 4) {?>Overlapping Clustering with Sparseness Constraints | event_type == 5) {?>11:20 - 11:45 | Overlapping Clustering with Sparseness Constraints Haibing Lu, Yuan Hong, Nick Street, Fei Wang, and Hanghang Tong |
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| 11:45 - 13:30 | Lunch Break |
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11:45 - 13:30 | Lunch Break |
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11:45 - 13:30 | Lunch Break | event_type == 4) {?>Lunch Break | event_type == 5) {?>11:45 - 13:30 | Lunch Break |
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| 13:30 - 14:30 | Invited Report Prof. Lieven De Lathauwer |
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13:30 - 14:30 | Invited Report Prof. Lieven De Lathauwer |
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13:30 - 14:30 | Invited Report | event_type == 4) {?>Invited Report | event_type == 5) {?>13:30 - 14:30 | Invited Report Prof. Lieven De Lathauwer |
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| 14:30 - 14:50 | Coffee Break |
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14:30 - 14:50 | Coffee Break |
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14:30 - 14:50 | Coffee Break | event_type == 4) {?>Coffee Break | event_type == 5) {?>14:30 - 14:50 | Coffee Break |
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| 14:50 - 15:10 | Rare Events Forecasting Using a Residual-Feedback GMDH Neural Network Simon Fong |
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14:50 - 15:10 | Rare Events Forecasting Using a Residual-Feedback GMDH Neural Network Simon Fong |
event_type == 3) {?>
14:50 - 15:10 | Rare Events Forecasting Using a Residual-Feedback GMDH Neural Network | event_type == 4) {?>Rare Events Forecasting Using a Residual-Feedback GMDH Neural Network | event_type == 5) {?>14:50 - 15:10 | Rare Events Forecasting Using a Residual-Feedback GMDH Neural Network Simon Fong |
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| 15:10 - 15:30 | OCCAMS - An Optimal Combinatorial Covering Algorithm for Multi-document Summarization Sashka Davis, Conroy John, and Judith Schlesinger |
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15:10 - 15:30 | OCCAMS - An Optimal Combinatorial Covering Algorithm for Multi-document Summarization Sashka Davis, Conroy John, and Judith Schlesinger |
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15:10 - 15:30 | OCCAMS - An Optimal Combinatorial Covering Algorithm for Multi-document Summarization | event_type == 4) {?>OCCAMS - An Optimal Combinatorial Covering Algorithm for Multi-document Summarization | event_type == 5) {?>15:10 - 15:30 | OCCAMS - An Optimal Combinatorial Covering Algorithm for Multi-document Summarization Sashka Davis, Conroy John, and Judith Schlesinger |
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| 15:30 - 15:50 | Learning from multiple annotators : when data is hard and annotators are unreliable Chirine Wolley and Mohamed Quafafou |
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15:30 - 15:50 | Learning from multiple annotators : when data is hard and annotators are unreliable Chirine Wolley and Mohamed Quafafou |
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15:30 - 15:50 | Learning from multiple annotators : when data is hard and annotators are unreliable | event_type == 4) {?>Learning from multiple annotators : when data is hard and annotators are unreliable | event_type == 5) {?>15:30 - 15:50 | Learning from multiple annotators : when data is hard and annotators are unreliable Chirine Wolley and Mohamed Quafafou |
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| 15:50 - 16:10 | Coffee Break |
event_type == 2) {?>
15:50 - 16:10 | Coffee Break |
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15:50 - 16:10 | Coffee Break | event_type == 4) {?>Coffee Break | event_type == 5) {?>15:50 - 16:10 | Coffee Break |
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| 16:10 - 16:30 | Nonlinear Unsupervised Feature Learning: How Local Similarities Lead to Global Coding Amirreza Shaban, Hamid R. Rabiee, Marzieh S. Tahaei, and Erfan Salavati |
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16:10 - 16:30 | Nonlinear Unsupervised Feature Learning: How Local Similarities Lead to Global Coding Amirreza Shaban, Hamid R. Rabiee, Marzieh S. Tahaei, and Erfan Salavati |
event_type == 3) {?>
16:10 - 16:30 | Nonlinear Unsupervised Feature Learning: How Local Similarities Lead to Global Coding | event_type == 4) {?>Nonlinear Unsupervised Feature Learning: How Local Similarities Lead to Global Coding | event_type == 5) {?>16:10 - 16:30 | Nonlinear Unsupervised Feature Learning: How Local Similarities Lead to Global Coding Amirreza Shaban, Hamid R. Rabiee, Marzieh S. Tahaei, and Erfan Salavati |
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| 16:30 - 16:50 | Robust Kernel Nonnegative Matrix Factorization Zhichen Xia, Chris Ding, and Edmond Chow |
event_type == 2) {?>
16:30 - 16:50 | Robust Kernel Nonnegative Matrix Factorization Zhichen Xia, Chris Ding, and Edmond Chow |
event_type == 3) {?>
16:30 - 16:50 | Robust Kernel Nonnegative Matrix Factorization | event_type == 4) {?>Robust Kernel Nonnegative Matrix Factorization | event_type == 5) {?>16:30 - 16:50 | Robust Kernel Nonnegative Matrix Factorization Zhichen Xia, Chris Ding, and Edmond Chow |
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| 16:50 - 17:10 | Regular Multiple Criteria Linear Programming for Semi-supervised Classification Zhiquan Qi, Yingjie Tian, and Yong Shi |
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16:50 - 17:10 | Regular Multiple Criteria Linear Programming for Semi-supervised Classification Zhiquan Qi, Yingjie Tian, and Yong Shi |
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16:50 - 17:10 | Regular Multiple Criteria Linear Programming for Semi-supervised Classification | event_type == 4) {?>Regular Multiple Criteria Linear Programming for Semi-supervised Classification | event_type == 5) {?>16:50 - 17:10 | Regular Multiple Criteria Linear Programming for Semi-supervised Classification Zhiquan Qi, Yingjie Tian, and Yong Shi |
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