JMLR Workshop and Conference Proceedings Volume 6: Causality: Objectives and Assessment (NIPS 2008) Supplemental Material Editors: Isabelle Guyon, Dominik Janzing, and Bernhard Schölkopf.

Website of the "Pot-Luck Challenge: Bring Your Own Problems! The datasets of the problems proposed can be downloaded for further research.

Fact Sheets for the Pot-Luck Challenge These fact sheets describe briefly the datasets and some of the methods used by the participants to solve the tasks of the challenge. Dataset name Domain Fact Sheets CYTO Protein signaling networks in human T-cells Learning Causal Protein-Signaling Network From Experimental Data. Ping He, Zhi Geng, Wei Yan, Zhihai Liu. Learning Causal Protein-Signaling Network. Jin Tian, Akshay Deepak. LOCANET Four tasks from genomics, socio-economics, and chemo-informatics. LOcal CAusal NETwork. Isabelle Guyon, Alexander Statnikov, Constantin Aliferis. A Strategy for Making Predictions Under Manipulation. Laura Brown, Ioannis Tsamardinos. PROMO Marketing Detecting simple causal effects in time series. Jean-Philippe Pellet. Results on the PASCAL PROMO challenge. Ivan Markovsky. Iterative Stepwise Selection and Threshold for Learning Causes in Time Series. Jianxin Yin, Shaopeng Wang, Wanlu Deng, Ya Hu, Zhi Geng. SEMI Manufacturing Manufacturing data: SEMI tool level fault isolation. Eugene Tuv. TIED Artificial task Pot-luck challenge: TIED. Eugene Tuv.

Challenge Datasets. All the datasets of the challenge are uploaded to the repository of the Causality Workbench and are available for download, as well as other problems used in other challenges.