• Publications
  • Influence
Ant colony system: a cooperative learning approach to the traveling salesman problem
TLDR
The results show that the ACS outperforms other nature-inspired algorithms such as simulated annealing and evolutionary computation, and it is concluded comparing ACS-3-opt, a version of the ACS augmented with a local search procedure, to some of the best performing algorithms for symmetric and asymmetric TSPs.
Ant Algorithms for Discrete Optimization
TLDR
An overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and the ant colony optimization (ACO) metaheuristic is presented.
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
TLDR
It is shown that MACS-VRPTW is competitive with the best known existing methods both in terms of solution quality and computation time and improves some of the best solutions known for a number of problem instances in the literature.
Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks
TLDR
This work uses deep max-pooling convolutional neural networks to detect mitosis in breast histology images using as context a patch centered on the pixel to classify each pixel in the images.
Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images
TLDR
This work addresses a central problem of neuroanatomy, namely, the automatic segmentation of neuronal structures depicted in stacks of electron microscopy images, using a special type of deep artificial neural network as a pixel classifier to segment biological neuron membranes.
AntHocNet: an adaptive nature-inspired algorithm for routing in mobile ad hoc networks
TLDR
AntHocNet is a hybrid algorithm, which combines reactive path setup with proactive path probing, maintenance and improvement, based on the nature-inspired ant colony optimisation framework, and its performance advantage is visible over a broad range of possible network scenarios.
Flexible, High Performance Convolutional Neural Networks for Image Classification
We present a fast, fully parameterizable GPU implementation of Convolutional Neural Network variants. Our feature extractors are neither carefully designed nor pre-wired, but rather learned in a
Deep, Big, Simple Neural Nets for Handwritten Digit Recognition
Good old online backpropagation for plain multilayer perceptrons yields a very low 0.35 error rate on the MNIST handwritten digits benchmark. All we need to achieve this best result so far are many
...
...