Search Results - "Karmitsa, Napsu"

Special Issue “Nonsmooth Optimization in Honor of the 60th Birthday of Adil M. Bagirov”: Foreword by Guest Editors by Karmitsa, Napsu, Taheri, Sona

“…Nonsmooth optimization refers to the general problem of minimizing (or maximizing) functions that have discontinuous gradients. This Special Issue contains six…”
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Bundle Enrichment Method for Nonsmooth Difference of Convex Programming Problems by Gaudioso, Manlio, Taheri, Sona, Bagirov, Adil M., Karmitsa, Napsu

“…The Bundle Enrichment Method (BEM-DC) is introduced for solving nonsmooth difference of convex (DC) programming problems. The novelty of the method consists of…”
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Nonsmooth Optimization-Based Hyperparameter-Free Neural Networks for Large-Scale Regression by Karmitsa, Napsu, Taheri, Sona, Joki, Kaisa, Paasivirta, Pauliina, Bagirov, Adil M., Mäkelä, Marko M.

“…In this paper, a new nonsmooth optimization-based algorithm for solving large-scale regression problems is introduced. The regression problem is modeled as…”
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Diagonal Bundle Method for Nonsmooth Sparse Optimization by Karmitsa, Napsu

“…We propose an efficient diagonal bundle method for sparse nonsmooth, possibly nonconvex optimization. The convergence of the proposed method is proved for…”
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Missing Value Imputation via Clusterwise Linear Regression by Karmitsa, Napsu, Taheri, Sona, Bagirov, Adil, Makinen, Pauliina

“…In this paper a new method of preprocessing incomplete data is introduced. The method is based on clusterwise linear regression and it combines two well-known…”
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Testing Different Nonsmooth Formulations of the Lennard–Jones Potential in Atomic Clustering Problems by Karmitsa, Napsu

“…A cluster is a group of identical molecules or atoms loosely bound by inter-atomic forces. The optimal geometry minimises the potential energy—usually modelled…”
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Clustering in large data sets with the limited memory bundle method by Karmitsa, Napsu, Bagirov, Adil M., Taheri, Sona

“…•A nonsmooth optimization based algorithm for solving the minimum sum-of-squares clustering problems is developed.•The proposed algorithm is tested and…”
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Predicting pairwise interaction affinities with ℓ 0 -penalized least squares–a nonsmooth bi-objective optimization based approach by Paasivirta, Pauliina, Numminen, Riikka, Airola, Antti, Karmitsa, Napsu, Pahikkala, Tapio

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New diagonal bundle method for clustering problems in large data sets by Karmitsa, Napsu, Bagirov, Adil M., Taheri, Sona

“…•A new algorithm for solving clustering problems is developed.•The problem is formulated as nonsmooth difference of convex programming problem.•The algorithm…”
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Clusterwise support vector linear regression by Joki, Kaisa, Bagirov, Adil M., Karmitsa, Napsu, Mäkelä, Marko M., Taheri, Sona

“…•The new model for solving clusterwise linear regression problems is introduced based on the combination of the support vector machines for regression and…”
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Robust piecewise linear L1-regression via nonsmooth DC optimization by Bagirov, Adil M, Taheri, Sona, Karmitsa, Napsu, Sultanova, Nargiz, Asadi, Soodabeh

“…Piecewise linear -regression problem is formulated as an unconstrained difference of convex (DC) optimization problem and an algorithm for solving this problem…”
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Robust piecewise linear L 1-regression via nonsmooth DC optimization by Bagirov, Adil M., Taheri, Sona, Karmitsa, Napsu, Sultanova, Nargiz, Asadi, Soodabeh

“…Piecewise linear -regression problem is formulated as an unconstrained difference of convex (DC) optimization problem and an algorithm for solving this problem…”
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A proximal bundle method for nonsmooth DC optimization utilizing nonconvex cutting planes by Joki, Kaisa, Bagirov, Adil M., Karmitsa, Napsu, Mäkelä, Marko M.

“…In this paper, we develop a version of the bundle method to solve unconstrained difference of convex (DC) programming problems. It is assumed that a DC…”
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Aggregate subgradient method for nonsmooth DC optimization by Bagirov, Adil M., Taheri, Sona, Joki, Kaisa, Karmitsa, Napsu, Mäkelä, Marko M.

“…The aggregate subgradient method is developed for solving unconstrained nonsmooth difference of convex (DC) optimization problems. The proposed method shares…”
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Method for solving generalized convex nonsmooth mixed-integer nonlinear programming problems by Eronen, Ville-Pekka, Kronqvist, Jan, Westerlund, Tapio, Mäkelä, Marko M., Karmitsa, Napsu

“…In this paper, we generalize the extended supporting hyperplane algorithm for a convex continuously differentiable mixed-integer nonlinear programming problem…”
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A generative model and a generalized trust region Newton method for noise reduction by Pulkkinen, Seppo, Mäkelä, Marko M., Karmitsa, Napsu

“…In practical applications related to, for instance, machine learning, data mining and pattern recognition, one is commonly dealing with noisy data lying near…”
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Globally Convergent Cutting Plane Method forNonconvex Nonsmooth Minimization by Karmitsa, Napsu, TanakaFilho, Mario, Herskovits, Jose

“…Nowadays, solving nonsmooth (not necessarily differentiable) optimization problems plays a very important role in many areas of industrial applications. Most…”
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A continuation approach to mode-finding of multivariate Gaussian mixtures and kernel density estimates by Pulkkinen, Seppo, Mäkelä, Marko Mikael, Karmitsa, Napsu

“…Gaussian mixtures (i.e. linear combinations of multivariate Gaussian probability densities) appear in numerous applications due to their universal ability to…”
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Limited memory bundle method for large bound constrained nonsmooth optimization: convergence analysis by Karmitsa, Napsu, Mäkelä, Marko M.

“…Practical optimization problems often involve nonsmooth functions of hundreds or thousands of variables. As a rule, the variables in such large problems are…”
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Globally Convergent Cutting Plane Method for Nonconvex Nonsmooth Minimization by Karmitsa, Napsu, Tanaka Filho, Mario, Herskovits, José

“…Nowadays, solving nonsmooth (not necessarily differentiable) optimization problems plays a very important role in many areas of industrial applications. Most…”
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