Improved bounds on the number of ternary square-free words.
Improved Bounds on Weak e-Nets for Convex Sets.
Improved expansion of random Cayley graphs.
Improved free-form modelling of scattered data by dynamic neural networks.
Improved inclusion-exclusion identities and inequalities based on a particular class of abstract tubes.
Improved inclusion-exclusion identities via closure operators.
Improved lower bounds on the approximability of the traveling salesman problem
Improved Lower Bounds on the Approximability of the Traveling Salesman Problem
This paper deals with lower bounds on the approximability of different subproblems of the Traveling Salesman Problem (TSP) which is known not to admit any polynomial time approximation algorithm in general (unless ). First of all, we present an improved lower bound for the Traveling Salesman Problem with Triangle Inequality, Delta-TSP for short. Moreover our technique, an extension of the method of Engebretsen [11], also applies to the case of relaxed and sharpened triangle inequality, respectively,...
Improvement to the cooperative rules methodology by using the ant colony system algorithm.
The cooperative rules (COR) methodology [2] is based on a combinatorial search of cooperative rules performed over a set of previously generated candidate rule consequents. It obtains accurate models preserving the highest interpretability of the linguistic fuzzy rule-based systems. Once the good behavior of the COR methodology has been proven in previous works, this contribution focuses on developing the process with a novel kind of metaheuristic algorithm: the ant colony system one. Thanks to...
Improving feature selection process resistance to failures caused by curse-of-dimensionality effects
The purpose of feature selection in machine learning is at least two-fold - saving measurement acquisition costs and reducing the negative effects of the curse of dimensionality with the aim to improve the accuracy of the models and the classification rate of classifiers with respect to previously unknown data. Yet it has been shown recently that the process of feature selection itself can be negatively affected by the very same curse of dimensionality - feature selection methods may easily over-fit...
Improving prediction of neural networks: a study of two financial prediction tasks.
Improving the classification of complexities.
Improving the generalization ability of neuro-fuzzy systems by ε-insensitive learning
A new learning method tolerant of imprecision is introduced and used in neuro-fuzzy modelling. The proposed method makes it possible to dispose of an intrinsic inconsistency of neuro-fuzzy modelling, where zero-tolerance learning is used to obtain a fuzzy model tolerant of imprecision. This new method can be called ε-insensitive learning, where, in order to fit the fuzzy model to real data, the ε-insensitive loss function is used. ε-insensitive learning leads to a model with minimal Vapnik-Chervonenkis...
Improving the genetic algorithm of SLAVE.
Impulse noise removal based on new hybrid conjugate gradient approach
Image denoising is a fundamental problem in image processing operations. In this paper, we present a two-phase scheme for the impulse noise removal. In the first phase, noise candidates are identified by the adaptive median filter (AMF) for salt-and-pepper noise. In the second phase, a new hybrid conjugate gradient method is used to minimize an edge-preserving regularization functional. The second phase of our algorithm inherits advantages of both Dai-Yuan (DY) and Hager-Zhang (HZ) conjugate gradient...
Imre Simon : an exceptional graduate student
This short note reviews the main contributions of the Ph.D. thesis of Imre Simon. His graduate work had major impact on algebraic theory of automata and thirty years later we are in a good position to appreciate how sensitive he was in selecting good problems, and how clever in solving them!
Imre Simon: an exceptional graduate student
This short note reviews the main contributions of the Ph.D. thesis of Imre Simon. His graduate work had major impact on algebraic theory of automata and thirty years later we are in a good position to appreciate how sensitive he was in selecting good problems, and how clever in solving them!
In memoriam: Philippe Flajolet, the father of analytic combinatorics
In memoriam: Philippe Flajolet, the father of analytic combinatorics
Incidental and state-dependent phenomena in robot problem solving