135 research outputs found

    Practical Interests, Relevant Alternatives, and Knowledge Attributions: an Empirical Study

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    In defending his interest-relative account of knowledge, Jason Stanley relies heavily on intuitions about several bank cases. We experimentally test the empirical claims that Stanley seems to make concerning our common-sense intuitions about these cases. Additionally, we test the empirical claims that Jonathan Schaffer seems to make, regarding the salience of an alternative, in his critique of Stanley. Our data indicate that neither raising the possibility of error nor raising stakes moves most people from attributing knowledge to denying it. However, the raising of stakes (but not alternatives) does affect the level of confidence people have in their attributions of knowledge. We argue that our data impugn what both Stanley and Schaffer claim our common-sense judgments about such cases are

    Channeling measurements of lattice disorder at the GaAs–InAs(100) heterojunction

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    Rutherford backscattering spectrometry (RBS) combined with channeling techniques has been used to analyze the lattice disorder present in InAs thin films less than 1 ”m thick grown on GaAs(100) substrates by molecular beam epitaxy (MBE). The axial channeling yields along [100], [110], and [111] reveal that roughly one quarter of the atoms in the thin films are out of registry with the InAs lattice at the heterojunction interface. The amount of lattice disorder decreases rapidly to undetectable (7% lattice mismatch between GaAs and InAs

    Against the identification of assertoric content with compositional value

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    This essay investigates whether the things we say are identical to the things our sentences mean. It is argued that these theoretical notions should be distinguished, since assertoric content does not respect the compositionality principle. As a paradigmatic example, Kaplan's formal language LD is shown to exemplify a failure of compositionality. It is demonstrated that by respecting the theoretical distinction between the objects of assertion and compositional values certain conflicts between compositionality and contextualism are avoided. This includes the conflict between eternalism and the semantics of tense, the embedding problems for contextualism about epistemic modals and taste claims, and the conflict between direct reference and the semantics of bound pronouns (and monstrous operators). After presenting the theoretical picture which distinguishes assertoric content from compositional semantic value, some objections to the picture are addressed. In so doing, the objection from King (Philos Perspect 17(1):195-246, 2003) stemming from apparent complications with the interaction of temporal expressions and attitude reports is assessed and shown to be non-threatening

    On the Bounds of Function Approximations

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    Within machine learning, the subfield of Neural Architecture Search (NAS) has recently garnered research attention due to its ability to improve upon human-designed models. However, the computational requirements for finding an exact solution to this problem are often intractable, and the design of the search space still requires manual intervention. In this paper we attempt to establish a formalized framework from which we can better understand the computational bounds of NAS in relation to its search space. For this, we first reformulate the function approximation problem in terms of sequences of functions, and we call it the Function Approximation (FA) problem; then we show that it is computationally infeasible to devise a procedure that solves FA for all functions to zero error, regardless of the search space. We show also that such error will be minimal if a specific class of functions is present in the search space. Subsequently, we show that machine learning as a mathematical problem is a solution strategy for FA, albeit not an effective one, and further describe a stronger version of this approach: the Approximate Architectural Search Problem (a-ASP), which is the mathematical equivalent of NAS. We leverage the framework from this paper and results from the literature to describe the conditions under which a-ASP can potentially solve FA as well as an exhaustive search, but in polynomial time.Comment: Accepted as a full paper at ICANN 2019. The final, authenticated publication will be available at https://doi.org/10.1007/978-3-030-30487-4_3

    Losing Confidence in Luminosity

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    A mental state is luminous if, whenever an agent is in that state, they are in a position to know that they are. Following Timothy Williamson’s Knowledge and Its Limits, a wave of recent work has explored whether there are any non-trivial luminous mental states. A version of Williamson’s anti-luminosity appeals to a safety- theoretic principle connecting knowledge and confidence: if an agent knows p, then p is true in any nearby scenario where she has a similar level of confidence in p. However, the relevant notion of confidence is relatively underexplored. This paper develops a precise theory of confidence: an agent’s degree of confidence in p is the objective chance they will rely on p in practical reasoning. This theory of confidence is then used to critically evaluate the anti-luminosity argument, leading to the surprising conclusion that although there are strong reasons for thinking that luminosity does not obtain, they are quite different from those the existing literature has considered. In particular, we show that once the notion of confidence is properly understood, the failure of luminosity follows from the assumption that knowledge requires high confidence, and does not require any kind of safety principle as a premis
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