92 research outputs found

    Second-order Democratic Aggregation

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    Aggregated second-order features extracted from deep convolutional networks have been shown to be effective for texture generation, fine-grained recognition, material classification, and scene understanding. In this paper, we study a class of orderless aggregation functions designed to minimize interference or equalize contributions in the context of second-order features and we show that they can be computed just as efficiently as their first-order counterparts and they have favorable properties over aggregation by summation. Another line of work has shown that matrix power normalization after aggregation can significantly improve the generalization of second-order representations. We show that matrix power normalization implicitly equalizes contributions during aggregation thus establishing a connection between matrix normalization techniques and prior work on minimizing interference. Based on the analysis we present {\gamma}-democratic aggregators that interpolate between sum ({\gamma}=1) and democratic pooling ({\gamma}=0) outperforming both on several classification tasks. Moreover, unlike power normalization, the {\gamma}-democratic aggregations can be computed in a low dimensional space by sketching that allows the use of very high-dimensional second-order features. This results in a state-of-the-art performance on several datasets

    Theory of Thermal Conductivity in High-Tc Superconductors below Tc: Comparison between Hole-Doped and Electron-Doped Systems

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    In hole-doped high-Tc superconductors, thermal conductivity increases drastically just below Tc, which has been considered as a hallmark of a nodal gap. In contrast, such a coherence peak in thermal conductivity is not visible in electron-doped compounds, which may indicate a full-gap state such as a (d+is)-wave state. To settle this problem, we study the thermal conductivity in the Hubbard model using the fluctuation-exchange (FLEX) approximation, which predicts that the nodal d-wave state is realized in both hole-doped and electron-doped compounds. The contrasting behavior of thermal conductivity in both compounds originates from the differences in the hot/cold spot structure. In general, a prominent coherence peak in thermal conductivity appears in line-node superconductors only when the cold spot exists on the nodal line.Comment: 5 pages, to be published in J. Phys. Soc. Jpn. Vol.76 No.

    On partial derivatives of multivariate Bernstein polynomials

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    It is shown that Bernstein polynomials for a multivariate function converge to this function along with partial derivatives provided that the latter derivatives exist and are continuous. This result may be useful in some issues of stochastic calculus

    On some functions which verify differential inequalities

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