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ORCID3. AMBN 2017: Kyoto, Japan
- Antti Hyttinen, Joe Suzuki, Brandon M. Malone:
Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2017, Kyoto, Japan, September 20-22, 2017. Proceedings of Machine Learning Research 73, PMLR 2017
Preface
- Joe Suzuki, Antti Hyttinen, Brandon M. Malone:
Advanced Methodologies for Bayesian Networks 2017: Preface. 1-2
Invited Papers
- Wray L. Buntine:
Backoff methods for estimating parameters of a Bayesian network. 3 - Kun Zhang:
Causal Learning and Machine Learning. 4 - Taisuke Sato:
Learning probability by comparison. 5 - John T. Halloran:
Analyzing Tandem Mass Spectra: A Graphical Models Perspective. 6 - Tomi Silander:
Hyperparameter sensitivity revisited. 7 - Marco Scutari:
Dirichlet Bayesian Network Scores and the Maximum Entropy Principle. 8-20
Contributed Papers
- Jose M. Peña:
Causal Effect Identification in Alternative Acyclic Directed Mixed Graphs. 21-32 - Jose M. Peña:
Learning Causal AMP Chain Graphs. 33-44 - Mauro Scanagatta, Giorgio Corani, Marco Zaffalon:
Improved Local Search in Bayesian Networks Structure Learning. 45-56 - Kazuki Natori, Masaki Uto, Maomi Ueno:
Consistent Learning Bayesian Networks with Thousands of Variables. 57-68 - Colin Lee, Peter van Beek:
An Experimental Analysis of Anytime Algorithms for Bayesian Network Structure Learning. 69-80 - Yun Zhou, Jiang Wang, Cheng Zhu, Weiming Zhang:
Multiple DAGs Learning with Non-negative Matrix Factorization. 81-92 - Zhigao Guo, Xiaoguang Gao, Ruohai Di:
Learning Bayesian Network Parameters with Domain Knowledge and Insufficient Data. 93-104 - Hei Chan:
Incorporating Uncertain Evidence Into Arithmetic Circuits Representing Probability Distributions. 105-116 - Masakazu Ishihata, Shan Gao, Shin-ichi Minato:
Fast Message Passing Algorithm Using ZDD-Based Local Structure Compilation. 117-128 - Norihito Yasuda, Teruji Sugaya, Shin-ichi Minato:
Fast Compilation of s-t Paths on a Graph for Counting and Enumeration. 129-140 - Peter J. F. Lucas, Giso H. Dal, Steffen Michels:
Reducing the Cost of Probabilistic Knowledge Compilation. 141-152 - Masaaki Nishino, Kei Amii, Akihiro Yamamoto:
On the Sizes of Decision Diagrams Representing the Set of All Parse Trees of a Context-free Grammar. 153-164 - Keisuke Yamazaki, Yoichi Motomura:
Hidden Node Detection between Two Observable Nodes Based on Bayesian Clustering. 165-175 - Aditya Jitta, Arto Klami:
Few-to-few Cross-domain Object Matching. 176-187 - Naoto Takahashi, Yuuji Ichisugi:
Restricted Quasi Bayesian Networks as a Prototyping Tool for Computational Models of Individual Cortical Areas. 188-199
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