Simplicity is not Truth-Indicative
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[1] N. Draper,et al. Applied Regression Analysis. , 1967 .
[2] Cullen Schaffer,et al. A Conservation Law for Generalization Performance , 1994, ICML.
[3] Daniel N. Osherson,et al. On Advancing Simple Hypotheses , 1990, Philosophy of Science.
[4] T. Kuhn,et al. The Structure of Scientific Revolutions , 1963 .
[5] N. Chater. The Search for Simplicity: A Fundamental Cognitive Principle? , 1999 .
[6] Ilya Gertsbakh,et al. Measurement theory for engineers , 2003 .
[7] Bruce Edmonds,et al. From KISS to KIDS - An 'Anti-simplistic' Modelling Approach , 2004, MABS.
[8] W. Cleveland,et al. Regression by local fitting: Methods, properties, and computational algorithms , 1988 .
[9] Judea Pearl,et al. ON THE CONNECTION BETWEEN THE COMPLEXITY AND CREDIBILITY OF INFERRED MODELS , 1978 .
[10] Geoffrey I. Webb. Further Experimental Evidence against the Utility of Occam's Razor , 1996, J. Artif. Intell. Res..
[11] M. Forster,et al. Model Selection in Science: The Problem of Language Variance , 1999, The British Journal for the Philosophy of Science.
[12] Mario Bunge,et al. The Myth Of Simplicity , 1963 .
[13] N. Goodman,et al. The Structure of Appearance. , 1953 .
[14] David M. Raup,et al. How Nature Works: The Science of Self-Organized Criticality , 1997 .
[15] Karl R. Popper. The Logic of Scientific Discovery. , 1977 .
[16] Pedro M. Domingos. Beyond Occam's Razor: Process-Oriented Evaluation , 2000, ECML.
[17] I. Good. Corroboration, Explanation, Evolving Probability, Simplicity and a Sharpened Razor , 1968, The British Journal for the Philosophy of Science.
[18] V. Vapnik,et al. Necessary and Sufficient Conditions for the Uniform Convergence of Means to their Expectations , 1982 .
[19] Peter D. Turney. The Curve Fitting Problem: A Solution1 , 1990, The British Journal for the Philosophy of Science.
[20] H. Akaike,et al. Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .
[21] Ming Li,et al. Philosophical Issues in Kolmogorov Complexity , 1992, ICALP.
[22] Albert Einstein. Relativity: The Special and the General Theory A Popular Exposition , 1920, Nature.
[23] P. Murphy. An Empirical Analysis of the Bene t of Decision Tree Size Biases as a Function of Concept Distribution , 1994 .
[24] Gary James Jason,et al. The Logic of Scientific Discovery , 1988 .
[25] David Miller,et al. Inference, method, and decision , 1977 .
[26] Malcolm R. Forster,et al. How to Tell When Simpler, More Unified, or Less Ad Hoc Theories will Provide More Accurate Predictions , 1994, The British Journal for the Philosophy of Science.
[27] Russell Greiner,et al. Exploring the Decision Forest: An Empirical Investigation of Occam's Razor in Decision Tree Induction , 1997 .
[28] David H. Wolpert,et al. The Lack of A Priori Distinctions Between Learning Algorithms , 1996, Neural Computation.
[29] J. Kemeny. Two Measures of Complexity , 1955 .
[30] W. Quine,et al. On simple theories of a complex world , 2004, Synthese.
[31] S. Moss,et al. A smart automated macroeconometric forecasting system , 1994 .