4 papers:
ICML-c2-2014-SatoN #analysis #approximate #equation #probability #process #using- Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process (IS, HN), pp. 982–990.
- ICML-2011-WellingT #learning #probability
- Bayesian Learning via Stochastic Gradient Langevin Dynamics (MW, YWT), pp. 681–688.
SAC-2003-MaI #using- Long Time Step Molecular Dynamics using Targeted Langevin Stabilization (QM, JAI), pp. 178–182.
ICPR-v2-2002-SeokL #algorithm #analysis #approach #difference #learning #probability- The Analysis of a Stochastic Differential Approach for Langevine Comepetitive Learning Algorithm (JS, JWL), pp. 80–83.
