JMLR Special Topic on Causality
Papers appearing in the special topic:
- Introduction to Causal Inference
- Peter Spirtes; 11(May):1643−1662, 2010.
[abs][pdf]
- 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]
- Properties of Monotonic Effects on Directed Acyclic Graphs
- Tyler J. VanderWeele, James M. Robins; 10(Mar):699−718, 2009.
[abs][pdf]
- Bayesian Network Structure Learning by Recursive Autonomy Identification
- Raanan Yehezkel, Boaz Lerner; 10(Jul):1527−1570, 2009.
[abs][pdf]
- Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation
- Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos; 11(Jan):171−234, 2010.
[abs][pdf]
- Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions
- Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos; 11(Jan):235−284, 2010.
[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]
- Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data (Machine Learning Open Source Software Paper)
- Abhik Shah, Peter Woolf; 10(Feb):159−162, 2009.
[abs][pdf] [code][mloss.org]
- 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]
- The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models
- Ricardo Silva, Zoubin Ghahramani; 10(Jun):1187−1238, 2009.
[abs][pdf]
- Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning
- Halbert White, Karim Chalak; 10(Aug):1759−1799, 2009.
[abs][pdf]
- Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure
- Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru Miyano; 11(Jan):285−310, 2010.
[abs][pdf]
- Continuous Time Bayesian Network Reasoning and Learning Engine
- Christian R. Shelton, Yu Fan, William Lam, Joon Lee, Jing Xu; 11(Mar):1137−1140, 2010.
[abs][pdf] [code][mloss.org]
- Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing
- Ryo Yoshida, Mike West; 11(May):1771−1798, 2010.
[abs][pdf]
