2014Statistics and Machine Learning Workshop

活動議程

9月11日(Thu.)
13:00 ~ 14:00	Registration
Time		Speakers	Title	Chair
14:00 ~ 14:10			Opening
14:10 ~ 15:10	Keynote Speech 1	Song-Chun Zhu 朱松純	Pursuing a unified statistical model for regimes of image patterns	Chun-houh Chen 陳君厚
15:10 ~ 15:40	Tea Break
15:40 ~ 17:10	Session 1	Yuh-Jye Lee 李育杰	Online nonlinear support vector machine for large-scale classification	Hung Chen 陳宏
		Kuo-Jung Lee 李國榮	An application of spatial Bayesian hierarchical model with variable selection to fMRI data
		Hsiang-Ling Hsu 許湘伶	Simultaneous selection of designs and models for optimal forecasting in possibly misspecified polynomial regressions

9 月12日(Fri.)
9:00 ~ 10:00	Special Lecture 1	Ying Nian Wu 吳英年	Hierarchical models of image patterns	Ker-Chau Li 李克昭
10:00 ~ 10:30	Tea Break
10:30 ~ 12:00	Session 2	Shou-De Lin 林守德	Transfer Recommendation: Matching users and items across domains for designing a better recommendation engine	Hsuan-Tien Lin 林軒田
		Henry Horng-Shing Lu 盧鴻興	Integration of Boolean and Bayesian networks
		Nicole Chen 陳琬萍	Bayesian method for support recovery in multivariate multi-response linear regression
12:00 ~ 13:30	Lunch
13:30 ~ 14:30	Special Lecture 2	Matt Tianfu Wu 吳田富	Learning to compute faster: bottom-up/top-down inference processes and near-optimal cost-sensitive decision policy	Fang Yu 郁方
14:30 ~ 15:30	Session 3	Ting-Li Chen 陳定立	Iterative estimation by self-updating process	Hsing-Kuo Kenneth Pao 鮑興國
14:30 ~ 15:30	Session 3	Kuan-Chu Peng 彭冠舉	Re-weighting the morphological diversity	Hsing-Kuo Kenneth Pao 鮑興國
15:30 ~ 16:00	Tea Break
16:00 ~ 17:00	Keynote speech 2	Song-Chun Zhu 朱松純	Understanding scenes/events by joint spatial, temporal and causal inference	Ching-Shui Cheng 鄭清水
17:00 ~ 17:10	Closing