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31The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network SearchIn W. H. Hsu, R. Joehanes & C. D. Page (eds.), Proceedings of IJCAI-2003 workshop on learning graphical models for computational genomics, . 2003.Various algorithms have been proposed for learning (partial) genetic regulatory networks through systematic measurements of differential expression in wild type versus strains in which expression of specific genes has been suppressed or enhanced, as well as for determining the most informative next experiment in a sequence. While the behavior of these algorithms has been investigated for toy examples, the full computational complexity of the problem has not received sufficient attention. We show…Read more
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68Reflectance spectroscopy is a standard tool for studying the mineral composition of rock and soil samples and for remote sensing of terrestrial and extraterrestrial surfaces. We describe research on automated methods of mineral identification from reflectance spectra and give evidence that a simple algorithm, adapted from a well-known search procedure for Bayes nets, identifies the most frequently occurring classes of carbonates with reliability equal to or greater than that of human experts. We…Read more
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165Some recent exchanges (Gebharter 2017a,2017b; Baumgartner and Cassini, 2023) concern whether composition can have conditional independence properties analogous to causal relations. If so, composition might sometimes be detectable by the application of causal search algorithms. The discussion has focused on a particular algorithm, PC (Spirtes and Glymour, 1991). PC is but one, and in many circumstances not the best, of a host of causal search algorithms that are candidates for methods of discover…Read more
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116Clark Glymour, Richard Scheines, Peter Spirtes and Kevin Kelly. Discovering Causal Structure: Artifical Intelligence, Philosophy of Science and Statistical Modeling
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24Android Epistemology (edited book)MIT Press. 1994.Readable and accessible collection of papers re thinking machines.
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5Getting to the Truth Through Conceptual RevolutionsPSA Proceedings of the Biennial Meeting of the Philosophy of Science Association 1990 (1): 89-96. 1990.[I]t would be absurd for us to hope that we can know more of any object than belongs to the possible experience of it or lay claim to the least knowledge of how anything not assumed to be an object of possible experience is determined according to the constitution that it has in itself.* * *It would be… a still greater absurdity if we conceded no things in themselves or declared our experience to be the only possible mode of knowing things….[Kant, Prolegomena to Any Future Metaphysics]A certain …Read more
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80What Language Dependence Problem? A Reply for Joyce to Fitelson on JoycePhilosophy of Science 79 (4): 561-574. 2012.In an essay recently published in this journal, Branden Fitelson argues that a variant of Miller’s argument for the language dependence of the accuracy of predictions can be applied to Joyce’s notion of accuracy of credences formulated in terms of scoring rules, resulting in a general potential problem for Joyce’s argument for probabilism. We argue that no relevant problem of the sort Fitelson supposes arises since his main theorem and his supporting arguments presuppose the validity of nonlinea…Read more
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45It is commonplace to encounter nonstationary or heterogeneous data, of which the underlying generating process changes over time or across data sets. Such a distribution shift feature presents both challenges and opportunities for causal discovery. In this paper we develop a principled framework for causal discovery from such data, called Constraint-based causal Discovery from Nonstationary/heterogeneous Data, which addresses two important questions. First, we propose an enhanced constraint-base…Read more
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231. Really Statistical Explanations and Genetic Drift Really Statistical Explanations and Genetic Drift (pp. 169-188)Philosophy of Science 80 (2): 169-188. 2013.Really statistical explanation is a hitherto neglected form of noncausal scientific explanation. Explanations in population biology that appeal to drift are RS explanations. An RS explanation supplies a kind of understanding that a causal explanation of the same result cannot supply. Roughly speaking, an RS explanation shows the result to be mere statistical fallout.
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217Confirmation and chaosPhilosophy of Science 69 (2): 256-265. 2002.Recently, Rueger and Sharp (1996) and Koperski (1998) have been concerned to show that certain procedural accounts of model confirmation are compromised by non‐linear dynamics. We suggest that the issues raised are better approached by considering whether chaotic data analysis methods allow for reliable inference from data. We provide a framework and an example of this approach.
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19Confirmation and ChaosPhilosophy of Science 69 (2): 256-265. 2002.Recently, Rueger and Sharp (1996) and Koperski (1998) have been concerned to show that certain procedural accounts of model confirmation are compromised by non-linear dynamics. We suggest that the issues raised are better approached by considering whether chaotic data analysis methods allow for reliable inference from data. We provide a framework and an example of this approach.
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163A Theory of Causal Learning in Children: Causal Maps and Bayes NetsPsychological Review 111 (1): 3-32. 2004.We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimen…Read more
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158Reasons as Causes in Bayesian EpistemologyJournal of Philosophy 104 (9): 464-474. 2007.In everyday matters, as well as in law, we allow that someone’s reasons can be causes of her actions, and often are. That correct reasoning accords with Bayesian principles is now so widely held in philosophy, psychology, computer science and elsewhere that the contrary is beginning to seem obtuse, or at best quaint. And that rational agents should learn about the world from energies striking sensory inputs nerves in people—seems beyond question. Even rats seem to recognize the difference betwee…Read more
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89Causal inferenceErkenntnis 35 (1-3). 1991.We have examined only a few of the basic questions about causal inference that result from Reichenbach's two principles. We have not considered what happens when the probability distribution is a mixture of distributions from different causal structures, or how unmeasured common causes can be detected, or what inferences can reliably be drawn about causal relations among unmeasured variables, or the exact advantages that experimental control offers. A good deal is known about these questions, an…Read more
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237Actual causation: a stone soup essaySynthese 175 (2): 169-192. 2010.We argue that current discussions of criteria for actual causation are ill-posed in several respects. (1) The methodology of current discussions is by induction from intuitions about an infinitesimal fraction of the possible examples and counterexamples; (2) cases with larger numbers of causes generate novel puzzles; (3) "neuron" and causal Bayes net diagrams are, as deployed in discussions of actual causation, almost always ambiguous; (4) actual causation is (intuitively) relative to an initial…Read more
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8Comorbid science?Behavioral and Brain Sciences 33 (2-3). 2010.We agree with Cramer et al.'s goal of the discovery of causal relationships, but we argue that the authors' characterization of latent variable models (as deployed for such purposes) overlooks a wealth of extant possibilities. We provide a preliminary analysis of their data, using existing algorithms for causal inference and for the specification of latent variable models
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Relevant evidenceIn Peter Achinstein (ed.), The concept of evidence, Oxford University Press. 1983.
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222Reply to Humphreys and Freedman's review of causation, prediction, and searchBritish Journal for the Philosophy of Science 48 (4): 555-568. 1997.
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54Space-time and synonymyPhilosophy of Science 49 (3): 463-477. 1982.In "The Epistemology of Geometry" Glymour proposed a necessary structural condition for the synonymy of two space-time theories. David Zaret has recently challenged this proposal, by arguing that Newtonian gravitational theory with a flat, non-dynamic connection (FNGT) is intuitively synonymous with versions of the theory using a curved dynamical connection (CNGT), even though these two theories fail to satisfy Glymour's proposed necessary condition for synonymy. Zaret allowed that if FNGT and C…Read more
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11The Berlin Group and the Philosophy of Logical Empiricism, Nickolay Milkov and Volker Peckhous, eds (review)Balkan Journal of Philosophy 6 (1): 72-75. 2014.
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28Causal Modeling, Explanation and Severe TestingIn Deborah G. Mayo & Aris Spanos (eds.), Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science, Cambridge University Press. pp. 331-375. 2010.
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60The Evaluation of Discovery: Models, Simulation and Search through “Big Data”Open Philosophy 2 (1): 39-48. 2019.A central theme in western philosophy was to find formal methods that can reliably discover empirical relationships and their explanations from data assembled from experience. As a philosophical project, that ambition was abandoned in the 20th century and generally dismissed as impossible. It was replaced in philosophy by neo-Kantian efforts at reconstruction and justification, and in professional statistics by the more limited ambition to estimate a small number of parameters in pre-specified h…Read more
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2Logic, Methodology and Philosophy of Science. Proceedings of the Thirteenth International Congress (edited book)King’s College Publications. 2009.
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32Halpern's Actual Causality is an extended development of an account of causal relations among individual events in the tradition that analyzes causation as difference making. The book is notable for its efforts at formal clarity, its exploration of "normality" conditions, and the wealth of examples it uses and whose provenance it traces. Unfortunately, the various normality conditions considered undermine the capacity of the basic theory to plausibly treat various cases Halpern considers, and th…Read more
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