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Multi-UAV forest area inspection path planning based on concave polygon region decomposition. [PDF]
Kang B, Wang C, Su Y, Zeng J.
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Nanographenic bowls based on contorted hexabenzocoronene: Synthesis, structure, and supramolecular assembly with fullerene C<sub>60</sub>. [PDF]
Sun Y +12 more
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Influence of deformation path on microstructure evolution during multi-step deformation of a high strength steel: experiments and FE analysis. [PDF]
Dhondapure P +3 more
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Study on electromagnetic characteristics of cylindrical hole defect in variable parameter traction motor shaft based on eddy current effect. [PDF]
Song M +7 more
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Framework for X-ray mirror surface shape fitting. [PDF]
Huang L +9 more
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Consistency in Concave Regression
For each $t$ in some subinterval $T$ of the real line let $F_t$ be a distribution function with mean $m(t)$. Suppose $m(t)$ is concave. Let $t_1, t_2, \cdots$ be a sequence of points in $T$ and let $Y_1, Y_2, \cdots$ be an independent sequence of random variables such that the distribution function of $Y_k$ is $F_{t_k}$. We consider estimators $m_n(t) =
D L Hanson
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On the Concavity of the Consumption Function [PDF]
At least since Keynes (1935), many economists have had the intuition that the marginal propensity to consume out of wealth declines as wealth increases. Nonetheless, standard perfect-certainty and certainty equivalent versions of intertemporal optimizing models of consumption imply a marginal propensity to consume that is unrelated to the level of ...
Carroll, Christopher D, Kimball, Miles S
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A REPRESENTATION RESULT FOR CONCAVE SCHUR CONCAVE FUNCTIONS
Mathematical Finance, 2005A representation result is provided for concave Schur concave functions on L∞(Ω). In particular, it is proven that any monotone concave Schur concave weakly upper semicontinuous function is the infinimum of a family of nonnegative affine combinations of Choquet integrals with respect to a convex continuous distortion of the underlying probability.
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Neural Computation, 2003
The concave-convex procedure (CCCP) is a way to construct discrete-time iterative dynamical systems that are guaranteed to decrease global optimization and energy functions monotonically. This procedure can be applied to almost any optimization problem, and many existing algorithms can be interpreted in terms of it.
Alan L. Yuille, Anand Rangarajan 0001
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The concave-convex procedure (CCCP) is a way to construct discrete-time iterative dynamical systems that are guaranteed to decrease global optimization and energy functions monotonically. This procedure can be applied to almost any optimization problem, and many existing algorithms can be interpreted in terms of it.
Alan L. Yuille, Anand Rangarajan 0001
openaire +3 more sources

