PSI_AGH_2022

Artykuły do referatu

  • Bahar Yaakob, S., Watada, J., & Fulcher, J. (2011). Structural learning of the Boltzmann machine and its application to life cycle management. Neurocomputing, 74(12-13), 2193-2200. doi: 10.1016/j.neucom.2011.02.018
  • A. DeGloria, P. Faraboschi and M. Olivieri, "Efficient implementation of the Boltzmann machine algorithm," in IEEE Transactions on Neural Networks, vol. 4, no. 1, pp. 159-163, Jan. 1993, doi: 10.1109/72.182711.
  • Xu L., Oja E. (1990) Improved simulated annealing, Boltzmann machine, and attributed graph matching. In: Almeida L.B., Wellekens C.J. (eds) Neural Networks. EURASIP 1990. Lecture Notes in Computer Science, vol 412. Springer, Berlin, Heidelberg. doi: 10.1007/3-540-52255-7_36
  • Ghojogh, B., Ghodsi, A., Karray, F., & Crowley, M. (2021). Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey. ArXiv:2107.12521 [Physics, Stat]. https://arxiv.org/abs/2107.12521
  • Ackley, D.H., Hinton, G.E. and Sejnowski, T.J. (1985), A Learning Algorithm for Boltzmann Machines. Cognitive Science, 9: 147-169. doi: 10.1207/s15516709cog0901_7