Isaac E. Lagaris

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A spatially constrained mixture model for image segmentation

Konstantinos Blekas, Aristidis Likas, Nikolas P. Galatsanos, Isaac E. Lagaris
IEEE Transactions on Neural Networks
2005

Gaussian mixture models (GMMs) constitute a well-known type of probabilistic neural networks. One of their many successful applications is in image segmentation, where spatially constrained mixture… (More)

Artificial neural networks for solving ordinary and partial differential equations

Isaac E. Lagaris, Aristidis Likas, Dimitrios I. Fotiadis
IEEE Trans. Neural Networks
1998

We present a method to solve initial and boundary value problems using artificial neural networks. A trial solution of the differential equation is written as a sum of two parts. The first part… (More)

Mixture model analysis of DNA microarray images

Konstantinos Blekas, Nikolas P. Galatsanos, Aristidis Likas, Isaac E. Lagaris
IEEE Transactions on Medical Imaging
2005

In this paper, we propose a new methodology for analysis of microarray images. First, a new gridding algorithm is proposed for determining the individual spots and their borders. Then, a Gaussian… (More)

Solving differential equations with genetic programming

Ioannis G. Tsoulos, Isaac E. Lagaris
Genetic Programming and Evolvable Machines
2006

A novel method for solving ordinary and partial differential equations, based on grammatical evolution is presented. The method forms generations of trial solutions expressed in an analytical closed… (More)

MEMPSODE: A global optimization software based on hybridization of population-based algorithms and local searches

Constantinos Voglis, Konstantinos E. Parsopoulos, Dimitris G. Papageorgiou, Isaac E. Lagaris, Michael N. Vrahatis
Computer Physics Communications
2012

Article history: Received 4 April 2011 Received in revised form 5 January 2012 Accepted 6 January 2012 Available online 12 January 2012

Towards "Ideal Multistart". A stochastic approach for locating the minima of a continuous function inside a bounded domain

Constantinos Voglis, Isaac E. Lagaris
Applied Mathematics and Computation
2009

A stochastic global optimization method based on Multistart is presented. In this, the local search is conditionally applied with a probability that takes in account the topology of the objective… (More)

Neural-network methods for boundary value problems with irregular boundaries

Isaac E. Lagaris, Aristidis Likas, Dimitris G. Papageorgiou
IEEE Trans. Neural Netw. Learning Syst.
2000

Partial differential equations (PDEs) with boundary conditions (Dirichlet or Neumann) defined on boundaries with simple geometry have been successfully treated using sigmoidal multilayer perceptrons… (More)

Stopping rules for box-constrained stochastic global optimization

Isaac E. Lagaris, Ioannis G. Tsoulos
Applied Mathematics and Computation
2008

We present three new stopping rules for Multistart based methods. The first uses a device that enables the determination of the coverage of the bounded search domain. The second is based on the… (More)

MinFinder: Locating all the local minima of a function

Ioannis G. Tsoulos, Isaac E. Lagaris
Computer Physics Communications
2006

A new stochastic clustering algorithm is introduced that aims to locate all the local minima of a multidimensional continuous and differentiable function inside a bounded domain. The accompanying… (More)

Split-Merge Incremental LEarning (SMILE) of Mixture Models

In this article we present an incremental method for building a mixture model. Given the desired number of clusters K ≥ 2, we start with a two-component mixture and we optimize the likelihood by… (More)

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