PPT-Applying Computational Causal Discovery

Applying Computational Causal Discovery in Biomedicine Greg Cooper University of Pittsburgh Richard Scheines Carnegie Mellon University 1132018 Outline Motivation Basics of Causal Graphical. Jean-Philippe Pellet. Andre . Ellisseeff. Presented by Na Dai. Motivation. Why structure . l. earning?. What are Markov blankets?. Relationship between feature selection and Markov blankets?. Previous work. Reversible Debugging. Ivan . Lanese. Focus research group. Computer Science . and Engineering Department. Univers. ity . of Bologna/INRIA. Bologna, Italy. Joint work with Elena Giachino (FOCUS) and Claudio Antares Mezzina (FBK Trento). Susan Athey, Stanford GSB. Based on joint work with Guido Imbens, Stefan Wager. References outside CS literature. Imbens and Rubin Causal Inference book (2015): synthesis of literature prior to big data/ML. Faculty of Physics, University of Vienna &. Institute . for Quantum Optics . and Quantum Information, Vienna . Mateus . Araujo. , . Cyril . Branciard, Fabio Costa, Adrian Feix. , Christina . Giarmatzi, Ognyan Oreshkov, Magdalena Zych. Ling . Ning. &. . Mayte. . Frias. . Senior Research Associates. Neil . Huefner. . Associate Director. Timo. Rico. Executive Director. Outline. Understanding causal effects. Methods for estimating causal effects. Assoc. . Prof. Dr. Şehnaz . Şahinkarakaş. Introduction to Causal-Comparative Research. A . causal-comparative. . study. is. a . study in which the researcher attempts to determine the cause, or reason, for pre-existing differences in groups of . Dr Steven Stillman. Senior Fellow, Motu . Adjunct Professor of Economics, Waikato. NIDEA Theme Leader, New Zealand’s individuals, families and households. Launch Symposium, November 24. th. 2010. The Importance of Experimental Evidence . . Richard Scheines. Philosophy, Machine Learning, . Human-Computer Interaction . Carnegie Mellon University. 2. Goals. Basic Familiarity with Causal Model Search: . What it is. What it can and cannot do. Authors: Kyu . Han . Koh et. al.. Presented . by : . Ali Anwar. ABOUT ME. B.Sc. Electrical Engineering, University of Engineering and Technology Lahore, Pakistan. M.Sc. Computer Engineering. , University of Engineering and Technology Lahore, . Distributed Systems. Lecture 14. Michael Freedman. 2. Linearizability. Eventual. Consistency models. Sequential. Causal. Lamport. clocks: C(a) < C(z) Conclusion: . None. Vector clocks: V(a) < V(z) Conclusion: . Presented by: Arvind Kouta. 1. Consistency Models. Strict Consistency: operations are executed in order of wall-clock time (NTP). Sequential Consistency: operations are executed in some global ordering (Total Ordering). : A Mechanist Perspective. Stuart Glennan. Butler . University. The singularist and generalist view of causation. The. generalist view: Particular events are causally related because they fall under general laws. Causal arguments are inductive arguments in which the conclusion is a claim that one thing causes another.. For example:. Clogged arteries cause heart attacks. A rough surface produces friction. Exercise during heat causes sweating. (. CCD. ). of Biomedical Knowledge from Big . Data. University of Pittsburgh. Carnegie Mellon . University. Pittsburgh Supercomputing . Center. Yale . University. PIs: . Greg Cooper, Ivet . Bahar, Jeremy Berg.