Clark Glymour

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克拉克 · 格里默(Clark N. Glymour)生于1942年,是卡内基梅隆大学哲学系的校友大学名誉教授。他也是佛罗里达人类和机器认知研究所(Florida Institute for Human and Machine Cognition)的高级研究科学家。[1]

格里默获得化学与哲学学士学位,毕业之后又致力于化学物理的研究,并于1969年在印第安纳大学获得科学哲学博士学位,他从事机器学习领域研究,特别致力于自动化因果推断方法论,人类因果判断心理学,数学心理学的研究。

工作经历

格里默是卡内基梅隆大学哲学系的创始人,古根海姆研究员(Guggenheim Fellow),行为科学高级研究中心研究员[2]Phi Beta Kappa联谊会讲师[3],美国科学促进会(AAAS)统计部门研究员[4]。格里默和他的合作者创造了贝叶斯网络的因果解释[5]。他的研究兴趣领域包括: 认识论(epistemology[6](尤其是 Android 认识论(Android epistemology))、机器学习(machine learning,)、自动推理(automated reasoning)、判断心理学(psychology of judgment)和数学心理学(mathematical psychology[7]。格里默对科学哲学的主要贡献之一是在贝叶斯概率(Bayesian probability)领域,特别是在他对贝叶斯“旧证据问题”的分析中[8][9]。格里默与彼得 · 斯皮尔茨(Peter Spirtes)和理查德 · 谢恩斯(Richard Scheines)合作,还开发了一种自动因果推理算法,以软件形式实现,命名为TETRAD[10]。采用多元统计数据作为输入,TETRAD 从所有可能的因果关系模型中快速搜索,并根据这些变量之间的条件依赖关系输出最合理的因果模型。该算法基于统计学、图论、科学哲学和人工智能的原理[11]

格里默获得了化学(chemistry)和哲学(philosophy)的本科学位。他研究生工作专注于化学物理学(chemical physics),并于1969年获得印第安纳大学( Indiana University)历史与科学哲学博士学位。

研究兴趣

格里默在20世纪70年代聚焦于科学哲学领域传统问题,尤其是科学理论确认的正式说明,在这个同时期,他又研究了广义相对论模型的哲学趣味性。

到了80年代,与约翰厄尔曼合作,进行在19世纪末20世纪初的精神病学和物理学研究的历史课题,曾教授一门关于弗洛伊德的课程,特别是狭义相对论和广义相对论的起源和检验。

在同一时期,格里默开始对在社会科学中寻找因果解释的自动化程序的可能性感兴趣。与他的学生,凯文 · 凯利,理查德 · 谢恩斯和彼得 · 斯皮尔特斯合作开发了重新确定线性潜在变量模型的自动启发式程序,后来在《发现因果结构》(学术出版社,1987)中有所描述。

同时,又与凯利合作,将戈尔德和普特南为学习递归枚举集和递归函数而发展的形式化学习理论扩展到学习形式化理论。凯利在他的精彩著作《可靠调查的逻辑》(牛津,1987)和随后的论文中继续并极大地扩展了这项工作。

到1990年,理查德 · 谢恩斯和彼得 · 斯皮尔特斯和格里默已经开发了贝叶斯网络的因果解释,并概述了一个研究计划: 找到一个可行的搜索算法,用于描述特征不可区分性,并且生成一种算法,用于预测干预部分特征的因果结构。这个项目在《因果关系,预测和搜索》(斯普林格,1993年; 第二版,麻省理工学院,2001年)和相关的工作中已经实现的,研究人员包括格里默的学生,微软的克里斯米克和华盛顿大学统计学的托马斯理查森。

目前的研究是将先前关于因果贝叶斯网络和形式学习理论的工作应用于各种各样的课题。第一项工作是与约瑟夫拉姆齐及美国宇航局埃莫斯研究中心的合作者进行合作,主要工作是从光谱中自动识别矿物成分。第二项工作是和计算系统生物学小组一起研究机器学习程序的可能性和局限性,从信使 RNA 浓度的测量中推断基因调控的方式。第三项工作是与几位心理学家和格里默以前的学生大卫 · 丹克斯合作,致力于因果推理心理学的数学方面的工作,这项工作最近总结在《心灵的箭头: 贝叶斯网络和心理学中的图形因果模型》(麻省理工学院,2003)一书中。此外,格里默最近一直在研究分布式数据集的学习算法,这些数据集具有不同但并非不相关的变量集,目的是学习出一种分类器用于少数情况和大量变量的数据,预测罕见事件,特别是森林火灾,以及气候遥相关的因果分析。

在因果研究之外,他偶尔也会写一些哲学论文,比如最近,《一元论》中的“工具概率”,和玛拉 · 哈勒尔在《科学哲学》中的“确认与混沌”。教学方面,在大部分情况下,负责教授本科生入门课程。最近,是在教授一门关于西方宗教历史的课程以及一门关于道德和公共政策的课程。除此之外,还在西佛罗里达大学的佛罗里达人类和机器认知研究所有一份工作,并在匹茨堡大学历史和科学哲学系有一份兼职。

研究领域

  • Computational & Philosophical Foundations
  • Knowledge Discovery, Data Science, Learning from Big Data

https://www.ihmc.us/research/computational-and-philosophical-foundations/

https://www.ihmc.us/research/knowledge-discovery-data-science-learning-from-big-data/

发表的成果

书籍

理论与证据,普林斯顿大学出版社,1980

检验整体医学,普罗米修斯出版社,1985

时空理论基础,明尼苏达大学出版社,1986年

发现因果结构,学术出版社,1987年

因果,预测与搜索,麻省理工学院出版社,2001

通过思考,麻省理工学院出版社,1994

机器人认识论,麻省理工学院/ AAAI出版社,1996年

心灵之箭: 贝叶斯网和心理学中的图形因果模型,麻省理工学院出版社,2001年

伽利略在匹兹堡,哈佛大学出版社,2010年

期刊论文

  • "The Evaluation of Discovery: Models, Simulation and Search through “Big Data”", Open Philosophy, 2019. Available on-line (Open Access): https://doi.org/10.1515/opphil-2019-0005
  • "When is a Brain Like the Planet?", Philosophy of Science, 2008.
  • (with David Danks) "Reasons as Causes in Bayesian Epistemology", Journal of Philosophy, 2008.
  • "Markov Properties and Quantum Experiments", in W. Demopoulos and I. Pitowsky, eds. Physical Theory and Its Interpretation: Essays in Honor of Jeffrey Bub, Springer 2006.
  • (with Chu, T. and David Danks) "Data Driven Methods for Granger Causality and Contemporaneous Causality with Non-Linear Corrections: Climate Teleconnection Mechanisms", 2004.
  • "Review of Phil Dowe and Paul Nordhoff: Cause and Chance: Causation in an Indeterministic World", Mind, 2005.
  • (with Eberhardt, Frederick, and Richard Scheines). "N-1 Experiments Suffice to Determine the Causal Relations Among N Variables", 2004.
  • (with F. Eberhardt and R. Scheines), "Log2(N) Experiments are Sufficient, and in the Worst Case Necessary, for Identifying Causal Structure", UAI Proceedings, 2005
  • (with Handley, Daniel, Nicoleta Serban, David Peters, Robert O'Doherty, Melvin Field, Larry Wasserman, Peter Spirtes, and Richard Scheines), "Evidence of systematic expressed sequence tag IMAGE clone cross-hybridization on cDNA microarrays", Genomics, Vol. 83, Issue 6 (June, 2004), 1169-1175.
  • (with Handley, Daniel, Nicoleta Serban, and David G. Peters). "Concerns About Unreliable Data from Spotted cDNA Microarrays Due to Cross-Hybridization and Sequence Errors", Statistical Applications in Genetics and Molecular Biology, Vol. 3, Issue 1 (October 6, 2004), Article 25.
  • "Comment on D. Lerner", "The Illusion of Conscious Will", Behavioral and Brain Sciences, in press.
  • "Review of Joseph E. Early, Sr. (Ed.): Chemical Explanation: Characteristics, Development, Autonomy", Philosophy of Science, Vol. 71, No. 3 (July, 2004), 415-418.
  • (with Spirtes, and Peter Glymour). "Causal Inference", Encyclopedia of Social Science, in press
  • "We believe in freedom of the will so that we can learn", Behavioral and Brain Sciences, Vol. 27, No. 5 (2004), 661-662.
  • "The Automation of Discovery", Daedelus, Vol. Winter (2004), 69-77.
  • (with Serban, Nicoleta, Larry Wasserman, David Peters, Peter Spirtes, Robert O'Doherty, Dan Handley, and Richard Scheines). "Analysis of microarray data for treated fat cells", (2003).
  • (with Danks, David, and Peter Spirtes). "The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search", (2003).
  • (with Silva, Ricardo, Richard Scheines, and Peter Spirtes). "Learning Measurement Models for Unobserved Variables", UAI '03, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence, August 7–10, 2003, Acapulco, Mexico (2003), 543-550.
  • (with Danks, David and Peter Spirtes). "The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search", Proceedings of IJCAI-2003 Workshop on Learning Graphical Models for Computational Genomics, (2003), 22-31.
  • (with Frank Wimberly, Thomas Heiman, and Joseph Ramsey). "Experiments on the Accuracy of Algorithms for Inferring the Structure of Genetic Regulatory Networks from Microarray Expression Levels", International Joint Conference on Artificial Intelligence Workshop, 2003
  • "A Semantics and Methodology for Ceteris Paribus Hypotheses", Erkenntnis, Vol. 57 (2002), 395-405.
  • "Review of James Woodward, Making Things Happen: A Theory of Causal Explanation", British Journal for Philosophy of Science, Vol. 55 (2004), 779-790.
  • (with Fienberg, Stephen, and Richard Scheines). "Expert statistical testimony and epidemiological evidence: the toxic effects of lead exposure on children", Journal of Econometrics, Vol 113 (2003), 33-48.
  • "Learning, prediction and causal Bayes Nets", Trends in Cognitive Sciences, Vol. 7, No. 1 (2003), 43-47.
  • (with Alison Gopnik, David M. Sobel, Laura E. Schulz, Tamar Kushnir, and David Danks). "A theory of causal learning in children: Causal maps and Bayes nets", Psychological Review, Vol. 111, No. 1 (2004).
  • "Freud, Kepler, and the clinical evidence", in R. Wollheim and J. Hopkins, eds. Philosophical Essays on Freud, Cambridge University Press 1982.
  • and many others dating back to 1970.
  • "The Evaluation of Discovery: Models, Simulation and Search through “Big Data”", Open Philosophy, 2019. Available on-line (Open Access): https://doi.org/10.1515/opphil-2019-0005
  • "When is a Brain Like the Planet?", Philosophy of Science, 2008.
  • (with David Danks) "Reasons as Causes in Bayesian Epistemology", Journal of Philosophy, 2008.
  • "Markov Properties and Quantum Experiments", in W. Demopoulos and I. Pitowsky, eds. Physical Theory and Its Interpretation: Essays in Honor of Jeffrey Bub, Springer 2006.
  • (with Chu, T. and David Danks) "Data Driven Methods for Granger Causality and Contemporaneous Causality with Non-Linear Corrections: Climate Teleconnection Mechanisms", 2004.
  • "Review of Phil Dowe and Paul Nordhoff: Cause and Chance: Causation in an Indeterministic World", Mind, 2005.
  • (with Eberhardt, Frederick, and Richard Scheines). "N-1 Experiments Suffice to Determine the Causal Relations Among N Variables", 2004.
  • (with F. Eberhardt and R. Scheines), "Log2(N) Experiments are Sufficient, and in the Worst Case Necessary, for Identifying Causal Structure", UAI Proceedings, 2005
  • (with Handley, Daniel, Nicoleta Serban, David Peters, Robert O'Doherty, Melvin Field, Larry Wasserman, Peter Spirtes, and Richard Scheines), "Evidence of systematic expressed sequence tag IMAGE clone cross-hybridization on cDNA microarrays", Genomics, Vol. 83, Issue 6 (June, 2004), 1169-1175.
  • (with Handley, Daniel, Nicoleta Serban, and David G. Peters). "Concerns About Unreliable Data from Spotted cDNA Microarrays Due to Cross-Hybridization and Sequence Errors", Statistical Applications in Genetics and Molecular Biology, Vol. 3, Issue 1 (October 6, 2004), Article 25.
  • "Comment on D. Lerner", "The Illusion of Conscious Will", Behavioral and Brain Sciences, in press.
  • "Review of Joseph E. Early, Sr. (Ed.): Chemical Explanation: Characteristics, Development, Autonomy", Philosophy of Science, Vol. 71, No. 3 (July, 2004), 415-418.
  • (with Spirtes, and Peter Glymour). "Causal Inference", Encyclopedia of Social Science, in press
  • "We believe in freedom of the will so that we can learn", Behavioral and Brain Sciences, Vol. 27, No. 5 (2004), 661-662.
  • "The Automation of Discovery", Daedelus, Vol. Winter (2004), 69-77.
  • (with Serban, Nicoleta, Larry Wasserman, David Peters, Peter Spirtes, Robert O'Doherty, Dan Handley, and Richard Scheines). "Analysis of microarray data for treated fat cells", (2003).
  • (with Danks, David, and Peter Spirtes). "The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search", (2003).
  • (with Silva, Ricardo, Richard Scheines, and Peter Spirtes). "Learning Measurement Models for Unobserved Variables", UAI '03, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence, August 7–10, 2003, Acapulco, Mexico (2003), 543-550.
  • (with Danks, David and Peter Spirtes). "The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search", Proceedings of IJCAI-2003 Workshop on Learning Graphical Models for Computational Genomics, (2003), 22-31.
  • (with Frank Wimberly, Thomas Heiman, and Joseph Ramsey). "Experiments on the Accuracy of Algorithms for Inferring the Structure of Genetic Regulatory Networks from Microarray Expression Levels", International Joint Conference on Artificial Intelligence Workshop, 2003
  • "A Semantics and Methodology for Ceteris Paribus Hypotheses", Erkenntnis, Vol. 57 (2002), 395-405.
  • "Review of James Woodward, Making Things Happen: A Theory of Causal Explanation", British Journal for Philosophy of Science, Vol. 55 (2004), 779-790.
  • (with Fienberg, Stephen, and Richard Scheines). "Expert statistical testimony and epidemiological evidence: the toxic effects of lead exposure on children", Journal of Econometrics, Vol 113 (2003), 33-48.
  • "Learning, prediction and causal Bayes Nets", Trends in Cognitive Sciences, Vol. 7, No. 1 (2003), 43-47.
  • (with Alison Gopnik, David M. Sobel, Laura E. Schulz, Tamar Kushnir, and David Danks). "A theory of causal learning in children: Causal maps and Bayes nets", Psychological Review, Vol. 111, No. 1 (2004).
  • "Freud, Kepler, and the clinical evidence", in R. Wollheim and J. Hopkins, eds. Philosophical Essays on Freud, Cambridge University Press 1982.
  • and many others dating back to 1970.

参考文献

  1. "Clark Glymour". Carnegie Mellon University. Retrieved December 16, 2019.
  2. "Awards and Elections, Fall 2019". Center for Advanced Study in Behavioral Sciences. Retrieved December 16, 2019.
  3. "Romanell-Phi Beta Kappa Professorship Past Winners". Phi Beta Kappa. Retrieved December 16, 2019.
  4. "Clark Glymour". American Academy of Arts and Sciences. Retrieved December 16, 2019.
  5. P. Spirtes, C. Glymour, R. Scheines, Causation, Prediction and Search, Springer Lecture Notes in Statistics, 1993.
  6. Epistemology: 5 Questions Edited by Vincent F. Hendricks and Duncan Pritchard, September 2008, ISBN 87-92130-07-0.
  7. "Clark Glymour". Retrieved December 16, 2019.
  8. "Bayesian Epistemology". July 12, 2001.
  9. Glymour, C.; Theory and evidence (1981), pp. 63-93.
  10. Publications TETRAD. Retrieved December 16, 2019.
  11. Glymour, Clark; Scheines, Richard; Spirtes, Peter; Kelly, Kevin. "TETRAD: Discovering Causal Structure" Multivariate Behavioral Research 23.2 (1988). 10 July 2010. doi:10.1207/s15327906mbr2302_13. PMID 26764954.

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