5 papers
Intuitive Analysis of the Quantization-based Optimization: From Stochastic and Quantum Mechanical Perspective
Jinwuk Seok, Changsik Cho
In this paper, we present an intuitive analysis of the optimization technique based on the quantization of an objective function. Quantization of an objective function is an effect…
Quantization-based Optimization with Perspective of Quantum Mechanics
Jinwuk Seok, Changsik Cho
Statistical and stochastic analysis based on thermodynamics has been the main analysis framework for stochastic global optimization. Recently, appearing quantum annealing or quantu…
Stochastic Gradient Langevin Dynamics Based on Quantization with Increasing Resolution
JInwuk Seok, Changsik Cho
Stochastic learning dynamics based on Langevin or Levy stochastic differential equations (SDEs) in deep neural networks control the variance of noise by varying the size of the min…
Quantization-Based Optimization: Alternative Stochastic Approximation of Global Optimization
Jinwuk Seok, Chang Sik Cho
In this study, we propose a global optimization algorithm based on quantizing the energy level of an objective function in an NP-hard problem. According to the white noise hypothes…
Stochastic Learning Equation using Monotone Increasing Resolution of Quantization
Jinwuk Seok, Jeong-Si Kim
In this paper, we propose a quantized learning equation with a monotone increasing resolution of quantization and stochastic analysis for the proposed algorithm. According to the w…