JMLR Special Topic on Causality
Papers appearing in the special topic:
- Using Markov Blankets for Causal Structure Learning
- Jean-Philippe Pellet, André Elisseeff; 9(Jul):1295--1342, 2008.
[abs][pdf]
- Causal Reasoning with Ancestral Graphs
- Jiji Zhang; 9(Jul):1437--1474, 2008.
[abs][pdf]
- Complete Identification Methods for the Causal Hierarchy
- Ilya Shpitser, Judea Pearl; 9(Sep):1941--1979, 2008.
[abs][pdf]
- Active Learning of Causal Networks with Intervention Experiments and Optimal Designs
- Yang-Bo He, Zhi Geng; 9(Nov):2523--2547, 2008.
[abs][pdf]
- Markov Properties for Linear Causal Models with Correlated Errors
- Changsung Kang, Jin Tian; 10(Jan):41--70, 2009.
[abs][pdf]
- Improving the Reliability of Causal Discovery from Small Data Sets Using Argumentation
- Facundo Bromberg, Dimitris Margaritis; 10(Feb):301--340, 2009.
[abs][pdf]
Related JMLR Papers:
- "Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks
- Gal Elidan, Iftach Nachman, Nir Friedman; 8(Aug):1799--1833, 2007.
[abs][pdf]
- A Recursive Method for Structural Learning of Directed Acyclic Graphs
- Xianchao Xie, Zhi Geng; 9(Mar):459--483, 2008.
[abs][pdf]
- Search for Additive Nonlinear Time Series Causal Models
- Tianjiao Chu, Clark Glymour; 9(May):967--991, 2008.
[abs][pdf]
- Finding Optimal Bayesian Network Given a Super-Structure
- Eric Perrier, Seiya Imoto, Satoru Miyano; 9(Oct):2251--2286, 2008.
[abs][pdf]
- Learning Bounded Treewidth Bayesian Networks
- Gal Elidan, Stephen Gould; 9(Dec):2699--2731, 2008.
[abs][pdf]
- Structural Learning of Chain Graphs via Decomposition
- Zongming Ma, Xianchao Xie, Zhi Geng; 9(Dec):2847--2880, 2008.
[abs][pdf]
- Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm (Special Topic on Mining and Learning with Graphs and Relations)
- Junning Li, Z. Jane Wang; 10(Feb):475--514, 2009.
[abs][pdf]
