Program
Nov. 18th
9:00-9:15 Opening
9:15-10:15 Keynote speech I
Chair: Maomi Ueno
Constraint Optimal Search on Learning Bayesian Network Structure
Seiya Imoto (University of Tokyo)
Coffee Break
Learning I
Chair: Joe Suzuki
10:35-11:00 Tao Chen, Nevin L. Zhang and Yi Wang
The Role of Operation Granularity in Search-Based Learning of Latent Tree Models
11:00-11:25 Masakazu Ishihata, Taisuke Sato and Shin-ishi Minato
Parameter Learning for Bayesian Networks on Shared Binary Decision Diagrams
11:25-11:50 Navid Bazzazzadeh
Modeling the Dynamic Topology of Bayesian Networks for Time Series Data
Lunch
Application I
Chair: Yoichi Motomura
13:40-14:05 Takamitsu Hashimoto and Maomi Ueno
Latent Conditional Independence Test for Bayesian Network IRT
14:05-14:30 Ronnie Johansson and Christian Mårtenson
Information Acquisition for General Bayesian Networks with Uncertain Observations
14:30-14:55 Koji Nomori, Yoshifumi Nishida, Yoichi Motomura and Tatsuhiro Yamanaka
Computational Prediction and Control of Injury Risk Using Bayesian Network
Coffee Break
15:20-16:20 Keynote speech II
Chair: Shin-ichi Minato
A Brief History of Belief Propagation
Arthur Choi (UCLA)
Application II
Chair: Neil Rubens
16:35-17:00 Leonard K. M. Poon, Nevin L. Zhang, Tao Chen, Tengfei Liu and Yi Wang
Using Bayesian Networks for Model-Based Multiple Clusterings: An Example of Exploratory Analysis on NBA Data
17:00-17:25 Yuuji Ichisugi
Parameter Learning of a Cerebral Cortex Model based on a Bayesian Network
17:25-17:50 Yoichi Motomura
Applied Human Modeling using Bayesian Networks in Service Engineering
19:00- Banquet
Nov. 19th
9:10-10:10 Keynote speech III
Chair: Taisuke Sato
Relax, Compensate and then Recover: A Theory of Anytime, Approximate Inference
Adnan Darwiche (UCLA)
Coffee Break
Reasoning
Chair: Neil Rubens
10:30-10:55 Shin-ichi Minato
Discrete Structure Manipulation System and Applications for Uncertain Data Processing
10:55-11:20 Kiyoharu Hamaguchi
MAP Inference on ZDD-based Representation of Bayesian Networks
11:20-11:45 Yu Nishiyama, Xingyao Ye and Alan Yuille
A Family of CCCP Algorithms which Minimize the TRW Free Energy
Lunch
13:10-14:10 Keynote speech IV
Chair: Kenji Yamanishi
Towards Objective Learning of Bayesian Networks
Petri Myllymäki (University of Helsinki)
Learning II
Chair: Takashi Isozaki
14:15-14:40 Joe Suzuki
Information Criteria and their Strong Consistency for Learning Bayesian Networks
14:40-15:05 Maomi Ueno
Optimal Dirichlet Prior for Bayesian Network
Coffee Break
Causality
Chair: Hei Chan
15:30-15:55 Fumiaki Kobayashi and Manabu Kuroki
Statistical Inference of Natural Direct and Indirect Effects and its Application
15:55-16:20 Doris Entner and Patrik O. Hoyer
Discovering Unconfounded Causal Relationships using Linear Non-Gaussian Models
16:20-16:45 Masaaki Nishino and Akihiro Yamamoto
Integrating Probabilistic Reasoning and Logic for Expressing Human Inference with Uncertainty
16:45-16:55 Closing