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Ant colony system: a cooperative learning approach to the traveling salesman problem
- M. Dorigo, L. Gambardella
- Computer ScienceIEEE Trans. Evol. Comput.
- 1 April 1997
TLDR
Ant Algorithms for Discrete Optimization
- M. Dorigo, G. D. Caro, L. Gambardella
- Computer ScienceArtificial Life
- 1 April 1999
TLDR
Ant colonies for the travelling salesman problem.
- M. Dorigo, L. Gambardella
- Computer ScienceBio Systems
- 1 July 1997
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
- L. Gambardella, É. Taillard, Giovanni Agazzi
- Computer Science
- 1999
TLDR
Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks
- D. Ciresan, A. Giusti, L. Gambardella, J. Schmidhuber
- Computer ScienceMICCAI
- 22 September 2013
TLDR
Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images
- D. Ciresan, A. Giusti, L. Gambardella, J. Schmidhuber
- Computer ScienceNIPS
- 3 December 2012
TLDR
Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem
- L. Gambardella, M. Dorigo
- Computer ScienceICML
- 9 July 1995
AntHocNet: an adaptive nature-inspired algorithm for routing in mobile ad hoc networks
- G. D. Caro, F. Ducatelle, L. Gambardella
- Computer ScienceEur. Trans. Telecommun.
- 1 September 2005
TLDR
Flexible, High Performance Convolutional Neural Networks for Image Classification
- D. Ciresan, U. Meier, Jonathan Masci, L. Gambardella, J. Schmidhuber
- Computer ScienceIJCAI
- 16 July 2011
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
- D. Ciresan, U. Meier, L. Gambardella, J. Schmidhuber
- Computer ScienceNeural Computation
- 1 March 2010
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…
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