Self-regular functions and new search directions for linear and semidefinite optimization In this paper, we introduce the notion of a self-regular function. Such a function is strongly convex and smooth coercive on its domain, the positive real ... J Peng,C Roos,T Terlaky - 《Mathematical P...
Tuan, H.N.: Linear convergence of a type of iterative sequences in nonconvex quadratic programming. J. Math. Anal. Appl. 423(2), 1311–1319 (2015) Article MathSciNet MATH Google Scholar Tuan, H.N., Yen, N.D.: Convergence of the Pham Dinh-Le Thi’s algorithm for the trust-regio...
Where :math:`f()` is the line search objective and :math:`x` the vector of parameter values [NocedalWright]_. It is important to note that approximate eigenvalue scaling does **not** *always* improve convergence, and that it can in fact *significantly* degrade performance for certain cla...
Sparse regularized low-rank tensor regression with applications in genomic data analysis Pattern Recognit. (2020) C.Blumet al. Beam search for the longest common subsequence problem Comput. Oper. Res. (2009) A.Apostolicoet al. Fast linear-space computations of longest common subsequences ...
Binary Search 004.Median-of-Two-Sorted-Arrays (H) 153.Find-Minimum-in-Rotated-Sorted-Array (M+) 154.Find-Minimum-in-Rotated-Sorted-Array-II (H-) 033.Search-in-Rotated-Sorted-Array (M) 081.Search-in-Rotated-Sorted-Array-II (M) 034.Search-for-a-Range (M) 162.Find-Peak-Element...
This allows for utilizing the simplicity of the greedy method while offsetting its limitations.Enroll in our C programming course to add a new skill to your skills bucket.What are the Components of the Greedy Algorithm?The greedy algorithm, known for its efficiency in problem-solving within ...
Integer linear programming (ILP) has long been an important tool for operations research akin to the AI search heuristics for NP-hard problems. However, th... J Eugene Santos - International Conference on Tools with Artificial Intelligence 被引量: 33发表: 1993年 Topics in computational linear op...
Instead, it is carried out iteratively in step c, which is repeated m times. Note that m can be selected in advance or adaptively during the algorithm. For instance, m can be chosen so that ∥um+1−um∥ is less than some prespecified tolerance that can vary with n. Recent studies ...
In this paper, we present a nonmonotone smoothing Newton algorithm for solving the circular cone programming(CCP) problem in which a linear function is minimized or maximized over the intersection of an affine space with the circular cone. Based on the relationship between the circular cone and th...
Larissa C. Shimomura, ... Daniel S. Kaster, in Information Systems, 2021 4 Construction algorithms for proximity graphs This section presents the existing construction algorithms for proximity graphs, which are listed in Table 2. In Table 2, we indicate for which graph type the algorithm was in...