Atsiliepimai
Formatai:
Aprašymas
Sure to be influential, Watanabe s book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.
Elektroninė knyga:
Atsiuntimas po užsakymo akimirksniu! Skirta skaitymui tik kompiuteryje, planšetėje ar kitame elektroniniame įrenginyje.
Kaip skaityti el. knygas ACSM formatu?
Mažiausia kaina per 30 dienų: 136,59 €
Mažiausia kaina užfiksuota: Kaina nesikeitė
Sure to be influential, Watanabe s book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.
Atsiliepimai