conjugate convex function

conjugate convex function的基本解释

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共轭凸函数

与conjugate convex function相关的网络例句 [注：此内容来源于网络，仅供参考]

In this paper, the computation of original likelihood function is transformed into the optimal problem of its low bound through the conjugate representation of the convex function, and a additional parameter is introduced to control the smoothing degree of low bound, and so the performance of local optimal solution can be improved.

我们利用凸泛函的对偶性，将原似然函数的复杂计算问题转化为对其下界函数的优化问题，从而降低学习算法的复杂性；并通过引入一个参数来控制下界函数的光滑程度来改善局部最优解的性能；指出了传统的期望最大化算法(Expectation Maximization Algorithm)是变分学习算法的特殊情况。

This paper presents a new algorithm for feed forward neural networks based on a new optimal target function constructed according to Young inequality in the conjugate of convex function.

提出的算法是利用凸函数共轭性质中的Young不等式构造优化目标函数，这个优化目标函数对于权值和隐层输出来说为凸函数，不存在局部最小。

Generalized strong vector variational-like inequalities; Minty's lemma; KKM mapping; pseudomonotone; Ky Fan lemma; open mapping theorem; complete; the second category; conjugate; proper convex lower semicontinuous function; linear mapping; closedness

基础科学，数学，数学分析广义强向量似变分不等式； Minty引理； KKM映象；伪单调； Ky Fan引理；开映射定理；完备；第二纲；共轭；真凸下半连续函数；线性映射；闭性

与conjugate convex function相关的网络解释 [注：此内容来源于网络，仅供参考]

conjugate convex function：共轭凸函数

conjugate complex number 共轭复数 | conjugate convex function 共轭凸函数 | conjugate curve 共轭曲线