convex optimization problem 凸优化问题
convex programming Problem 凸性规划问题
highly non-convex optimization problem 高度非凸的优化问题
Convex Hulls Problem 凸包问题
convex quadratic programming problem [数] 凸二次规划问题
These two algorithms relax the constraints of ML algorithm and transform it into a convex problem which can be efficiently solved with a polynomial time.
这两类算法是在ML算法基础上放松约束条件，将问题转化为可在多项式时间内解决的凸优化问题。
The convexity of curves and surfaces is an important property in the field of Computer Aided Geometric Design (CAGD). This paper tries to tackle the positive and convex problem of polynomials.
在计算机辅助几何设计(CAGD)中，曲面曲线的凸性是一种重要的特性旨在解决多项式的正性和凸性问题。
The proposed method transforms the training problem into a number of convex subproblems which can be solved in shorter time to obtain globally solutions.
该方法将网络训练问题变换为一系列的凸规划子问题，而这些子问题都可以在较短时间内获得全局最优解。
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