Robust Multicategory Support Vector Machines using Difference Convex Algorithm [0.03%]
基于差凸算法的稳健多类支持向量机方法研究
Chong Zhang,Minh Pham,Sheng Fu et al.
Chong Zhang et al.
The Support Vector Machine (SVM) is one of the most popular classification methods in the machine learning literature. Binary SVM methods have been extensively studied, and have achieved many successes in various disciplines. However, gener...
Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions [0.03%]
折叠凹面惩罚稀疏线性回归：局部解的稀疏性、统计性能和算法理论
Hongcheng Liu,Tao Yao,Runze Li et al.
Hongcheng Liu et al.
This paper concerns the folded concave penalized sparse linear regression (FCPSLR), a class of popular sparse recovery methods. Although FCPSLR yields desirable recovery performance when solved globally, computing a global solution is NP-co...
Approximating the Little Grothendieck Problem over the Orthogonal and Unitary Groups [0.03%]
正交群和酉群下的小Grothendieck问题的近似算法
Afonso S Bandeira,Christopher Kennedy,Amit Singer
Afonso S Bandeira
The little Grothendieck problem consists of maximizing Σ ij Cijxixj for a positive semidef-inite matrix C, over binary variables xi ∈ {±1}. In this paper we focus on a natural generalization of this problem, the little Grothendieck probl...
Donghwan Kim,Jeffrey A Fessler
Donghwan Kim
We introduce new optimized first-order methods for smooth unconstrained convex minimization. Drori and Teboulle [5] recently described a numerical method for computing the N-iteration optimal step coefficients in a class of first-order algo...
Eric C Chi,Hua Zhou,Kenneth Lange
Eric C Chi
The problem of minimizing a continuously differentiable convex function over an intersection of closed convex sets is ubiquitous in applied mathematics. It is particularly interesting when it is easy to project onto each separate set, but n...
Kenneth Lange,Hua Zhou
Kenneth Lange
This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-a...