5 papers
Progressive Weight Loading: Accelerating Initial Inference and Gradually Boosting Performance on Resource-Constrained Environments
Hyunwoo Kim, Junha Lee, Mincheol Choi +2
Deep learning models have become increasingly large and complex, resulting in higher memory consumption and computational demands. Consequently, model loading times and initial inf…
Scaling Limit of Dependent Random Walk
Jeonghwa Lee
Recently, a generalized Bernoulli process (GBP) was developed as a stationary binary sequence that can have long-range dependence. In this paper, we find the scaling limit of a ran…
Fractional binomial regression model for count data with excess zeros
Jeonghwa Lee, Chloe Breece
This paper proposes a new generalized linear model with the fractional binomial distribution. Zero-inflated Poisson/negative binomial distributions are used for count data with man…
On the construction of stationary processes and random fields
Jeonghwa Lee
We propose a new method to construct a stationary process and random field with a given decreasing covariance function and any one-dimensional marginal distribution. The result is…
Generalized Bernoulli Process and Fractional Binomial Distribution
Jeonghwa Lee
Recently, a generalized Bernoulli process (GBP) was developed as a stationary binary sequence whose covariance function obeys a power law. In this paper, we further develop general…