Zobrazeno 1 - 10
of 100
pro vyhledávání: '"Jeong, Seonghyun"'
Probabilistic mixture models are recognized as effective tools for unsupervised outlier detection owing to their interpretability and global characteristics. Among these, Dirichlet process mixture models stand out as a strong alternative to conventio
Externí odkaz:
http://arxiv.org/abs/2401.00773
Autor:
Lim, Sunwoo, Jeong, Seonghyun
Bayesian P-splines and basis determination through Bayesian model selection are both commonly employed strategies for nonparametric regression using spline basis expansions within the Bayesian framework. Although both methods are widely employed, the
Externí odkaz:
http://arxiv.org/abs/2311.13481
Autor:
Kang, Gyeonghun, Jeong, Seonghyun
We explore the estimation of generalized additive models using basis expansion in conjunction with Bayesian model selection. Although Bayesian model selection is useful for regression splines, it has traditionally been applied mainly to Gaussian regr
Externí odkaz:
http://arxiv.org/abs/2301.10468
In the analysis of binary longitudinal data, it is of interest to model a dynamic relationship between a response and covariates as a function of time, while also investigating similar patterns of time-dependent interactions. We present a novel gener
Externí odkaz:
http://arxiv.org/abs/2210.10273
Convolutional neural networks (CNNs) provide flexible function approximations for a wide variety of applications when the input variables are in the form of images or spatial data. Although CNNs often outperform traditional statistical models in pred
Externí odkaz:
http://arxiv.org/abs/2210.09560
Autor:
Ko, Minji, Kim, Soyeon, Jeong, Yujeong, Oh, Yeongbeen, Jeong, Seonghyun, Lee, Keyong Nam, Park, Younghoon, Song, Jae Kyu, Do, Young Rag
Publikováno v:
In Applied Surface Science 1 February 2025 681
Autor:
Jeong, Seonghyun
This paper studies posterior contraction rates in multi-category logit models with priors incorporating group sparse structures. We consider a general class of logit models that includes the well-known multinomial logit models as a special case. Grou
Externí odkaz:
http://arxiv.org/abs/2010.03513
Autor:
Jeong, Seonghyun, Ghosal, Subhashis
We study frequentist asymptotic properties of Bayesian procedures for high-dimensional Gaussian sparse regression when unknown nuisance parameters are involved. Nuisance parameters can be finite-, high-, or infinite-dimensional. A mixture of point ma
Externí odkaz:
http://arxiv.org/abs/2008.10230
Autor:
Jeong, Seonghyun, Rockova, Veronika
Many asymptotically minimax procedures for function estimation often rely on somewhat arbitrary and restrictive assumptions such as isotropy or spatial homogeneity. This work enhances the theoretical understanding of Bayesian additive regression tree
Externí odkaz:
http://arxiv.org/abs/2008.06620
We provide a flexible framework for selecting among a class of additive partial linear models that allows both linear and nonlinear additive components. In practice, it is challenging to determine which additive components should be excluded from the
Externí odkaz:
http://arxiv.org/abs/2008.06213