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  1. Reliability and Interpretability in Science and Deep Learning.Luigi Scorzato - 2024 - Minds and Machines 34 (3):1-31.
    In recent years, the question of the reliability of Machine Learning (ML) methods has acquired significant importance, and the analysis of the associated uncertainties has motivated a growing amount of research. However, most of these studies have applied standard error analysis to ML models—and in particular Deep Neural Network (DNN) models—which represent a rather significant departure from standard scientific modelling. It is therefore necessary to integrate the standard error analysis with a deeper epistemological analysis of the possible differences between DNN (...)
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  • Simple is not easy.Edison Barrios - 2016 - Synthese 193 (7):2261-2305.
    I review and challenge the views on simplicity and its role in linguistics put forward by Ludlow. In particular, I criticize the claim that simplicity—in the sense pertinent to science—is nothing more than ease of use or “user-friendliness”, motivated by economy of labor. I argue that Ludlow’s discussion fails to do justice to the diversity of factors that are relevant to simplicity considerations. This, in turn, leads to the neglect of crucial cases in which the rationale for simplification is unmistakably (...)
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  • Objectivity and Bias.Gordon Belot - 2017 - Mind 126 (503):655-695.
    The twin goals of this essay are: to investigate a family of cases in which the goal of guaranteed convergence to the truth is beyond our reach; and to argue that each of three strands prominent in contemporary epistemological thought has undesirable consequences when confronted with the existence of such problems. Approaches that follow Reichenbach in taking guaranteed convergence to the truth to be the characteristic virtue of good methods face a vicious closure problem. Approaches on which there is a (...)
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  • Simplicity: A unifying principle in cognitive science?Nick Chater & Paul Vitányi - 2003 - Trends in Cognitive Sciences 7 (1):19-22.
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  • Iterated belief revision, reliability, and inductive amnesia.Kevin T. Kelly - 1999 - Erkenntnis 50 (1):11-58.
    Belief revision theory concerns methods for reformulating an agent's epistemic state when the agent's beliefs are refuted by new information. The usual guiding principle in the design of such methods is to preserve as much of the agent's epistemic state as possible when the state is revised. Learning theoretic research focuses, instead, on a learning method's reliability or ability to converge to true, informative beliefs over a wide range of possible environments. This paper bridges the two perspectives by assessing the (...)
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  • The simplicity of theories: Its degree and form. [REVIEW]James W. McAllister - 1991 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 22 (1):1-14.
    Almost all commentators acknowledge that among the grounds on which scientists perform theory-choices are criteria of simplicity. In general, simplicity is regarded either as only a logico-empirical quality of a theory, diagnostic of the theory's future predictive success, or as a purely aesthetic or otherwise extra-empirical property of it. This paper attempts to demonstrate that the simplicity-criteria applied in scientific practice include both a logico-empirical and a quasi-aesthetic criterion: to conflate these in an account of scientists' theory-choice is to court (...)
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  • Inductive simplicity.Robert Ackermann - 1961 - Philosophy of Science 28 (2):152-161.
    The fact that simplicity has been linked with induction by many philosophers of science, some of whom have proposed or supported criteria of “inductive simplicity,” means that the problem must be given some serious attention. I take “inductive simplicity” as a title, however, only by way of concession to these historical treatments, since it is precisely the burden of my paper to show that there is no such thing. So much for the conclusion. I shall spend the remainder of my (...)
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  • Inductive learning by machines.Stuart Russell - 1991 - Philosophical Studies 64 (October):37-64.
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  • Syntactic Measures of Complexity.Bruce Edmonds - unknown
    1.1 - Background - page 17 1.2 - The Style of Approach - page 18 1.3 - Motivation - page 19 1.4 - Style of Presentation - page 20 1.5 - Outline of the Thesis - page 21..
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  • A paradigm-based solution to the Riddle of induction.Mark A. Changizi & Timothy P. Barber - 1998 - Synthese 117 (3):419-484.
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  • Induction: The glory of science and philosophy.Uwe Saint-Mont - unknown
    The aim of this contribution is to provide a rather general answer to Hume's problem, the well-known problem of induction. To this end, it is very useful to apply his differentiation between ``relations of ideas'' and ``matters of fact'', and to reconsider earlier approaches. In so doing, we consider the problem formally, as well as empirically. Next, received attempts to solve the problem are discussed. The basic structure of inductive problems is exposed in chap. 6. Our final conclusions are to (...)
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  • Crustal layering, simplicity, and the oil industry: The alteration of an epistemic paradigm by a commercial environment.Aitor Anduaga - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (4):322-345.
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  • On the concept of systematization in the Kemeny-Oppenheim approach to intertheoretical reduction.Gerhard Wagner - 2024 - Studies in History and Philosophy of Science Part A 103 (C):29-38.
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  • Induction: A Logical Analysis.Uwe Saint-Mont - 2022 - Foundations of Science 27 (2):455-487.
    The aim of this contribution is to provide a rather general answer to Hume’s problem. To this end, induction is treated within a straightforward formal paradigm, i.e., several connected levels of abstraction. Within this setting, many concrete models are discussed. On the one hand, models from mathematics, statistics and information science demonstrate how induction might succeed. On the other hand, standard examples from philosophy highlight fundamental difficulties. Thus it transpires that the difference between unbounded and bounded inductive steps is crucial: (...)
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  • An introduction to simplicity.Richard Rudner - 1961 - Philosophy of Science 28 (2):109-119.
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  • Gruesome simplicity.Graham Priest - 1976 - Philosophy of Science 43 (3):432-437.
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  • A theory and methodology of inductive learning.Ryszard S. Michalski - 1983 - Artificial Intelligence 20 (2):111-161.
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  • Unifying foundations – to be seen in the phenomenon of language.Lars Löfgren - 2004 - Foundations of Science 9 (2):135-189.
    Scientific knowledge develops in an increasingly fragmentary way.A multitude of scientific disciplines branch out. Curiosity for thisdevelopment leads into quests for a unifying understanding. To a certain extent, foundational studies provide such unification. There is a tendency, however, also of a fragmentary growth of foundational studies, like in a multitude of disciplinaryfoundations. We suggest to look at the foundational problem, not primarily as a search for foundations for one discipline in another, as in some reductionist approach, but as a steady (...)
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  • Analyticity versus fuzziness.John G. Kemeny - 1963 - Synthese 15 (1):57 - 80.
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  • Notes on probability and induction.Rudolf Carnap - 1973 - Synthese 25 (3-4):269 - 298.
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  • Diagnostic Parsimony.Bengt Autzen - 2022 - Philosophy of Medicine 3 (1).
    Ockham’s razor is the idea that simpler hypotheses are to be preferred over more complex ones. In the context of medical diagnosis, this is taken to mean that when a patient has multiple symptoms, a single diagnosis should be sought that accounts for all the clinical features, rather than attributing a different diagnosis to each. This paper examines whether diagnostic parsimony can be justified by reference to probability theory. I argue that while attempts to offer universal justifications of diagnostic parsimony (...)
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  • Crustal layering, simplicity, and the oil industry: The alteration of an epistemic paradigm by a commercial environment.Aitor Anduaga - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (4):322-345.
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