Results 11 to 20 of about 10,474 (140)
Polyhedral conic kernel-like functions for SVMs
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2019 In this study, we propose a new approach that can be used as a kernel-like function for support vector machines (SVMs) in order to get nonlinear classification surfaces. We combined polyhedral conic functions (PCFs) with the SVM method.
Gurkan Ozturk, Emre Çimen
semanticscholar +2 more sources
A Binary Classification Approach Based On Support Vector Machines Via Polyhedral Conic Functions
Celal Bayar Üniversitesi Fen Bilimleri Dergisi, 2016 A Binary Classification Approach Based On Support Vector Machines Via Polyhedral Conic Functions Classification is a frequently used technique of data mining. Binary classification is a type of classification that includes two classes. This problem has a
Nur Uylas Sati
semanticscholar +4 more sources
A Binary Classification Algorithm Based on Polyhedral Conic Functions
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2015 Data classification is one of the main techniques of data mining. Different mathematical programming approaches of the data classification were presented in recent years.
Nur Uylaş Satı
doaj +1 more source
Clustering based polyhedral conic functions algorithm in classification
Journal of Industrial & Management Optimization, 2014 In this study, a new algorithm based on polyhedral conic functions (PCFs) is developed to solve multi-class supervised data classification problems. The $k$ PCFs are constructed for each class in order to separate it from the rest of the data set. The $k$-means algorithm is applied to find vertices of PCFs and then a linear programming model is solved ...
Gurkan Ozturk, Mehmet Tahir Ciftci
semanticscholar +3 more sources
Effective Condition Number Bounds for Convex Regularization [PDF]
, 2019 We derive bounds relating Renegar's condition number to quantities that govern the statistical performance of convex regularization in settings that include the $\ell_1$-analysis setting.
Amelunxen, Dennis +2 more
core +2 more sources
Integrity Constraints Revisited: From Exact to Approximate Implication [PDF]
, 2019 Integrity constraints such as functional dependencies (FD), and multi-valued dependencies (MVD) are fundamental in database schema design. Likewise, probabilistic conditional independences (CI) are crucial for reasoning about multivariate probability ...
Kenig, Batya, Suciu, Dan
core +2 more sources
Bad semidefinite programs: they all look the same [PDF]
, 2017 Conic linear programs, among them semidefinite programs, often behave pathologically: the optimal values of the primal and dual programs may differ, and may not be attained. We present a novel analysis of these pathological behaviors.
Bauschke H. +6 more
core +3 more sources
Extended Formulations in Mixed-integer Convex Programming
, 2016 We present a unifying framework for generating extended formulations for the polyhedral outer approximations used in algorithms for mixed-integer convex programming (MICP).
A Ahmadi +19 more
core +1 more source
On the Aubin property of a class of parameterized variational systems [PDF]
, 2017 The paper deals with a new sharp criterion ensuring the Aubin property of solution maps to a class of parameterized variational systems. This class includes parameter-dependent variational inequalities with non-polyhedral constraint sets and also ...
Gfrerer, Helmut, Outrata, Jiří V
core +3 more sources
Polyhedral approximation in mixed-integer convex optimization
, 2017 Generalizing both mixed-integer linear optimization and convex optimization, mixed-integer convex optimization possesses broad modeling power but has seen relatively few advances in general-purpose solvers in recent years.
Bent, Russell +3 more
core +1 more source