Local Optima in Mixture Modeling
نویسندگان
چکیده
منابع مشابه
Avoiding spurious local maximizers in mixture modeling
The maximum likelihood estimation in the finite mixture of distributions setting is an ill-posed problem that is treatable, in practice, through the EM algorithm. However, the existence of spurious solutions (singularities and non-interesting local maximizers) makes difficult to find sensible mixture fits for non-expert practitioners. In this work, a constrained mixture fitting approach is pres...
متن کاملExploring Local Optima in Schematic Layout
Abstract—In search-based graph drawing methods there are typically a number of parameters that control the search algorithm. These parameters do not affect the fitness function, but nevertheless have an impact on the final layout. One such search method is hill climbing, and, in the context of schematic layout, we explore how varying three parameters (grid spacing, the starting distance of allo...
متن کاملOn Local Optima in Learning Bayesian Networks
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that it allows a trade-off between greediness and randomness, thus exploring different good local optima when run repeatedly. When greediness is set at maximum, KES corresponds to the greedy equivalence search algorithm (GES...
متن کاملLeaving Local Optima in Unsupervised Kernel Regression
Abstract. Embedding high-dimensional patterns in low-dimensional latent spaces is a challenging task. In this paper, we introduce re-sampling strategies to leave local optima in the data space reconstruction error (DSRE) minimization process of unsupervised kernel regression (UKR). For this sake, we concentrate on a hybrid UKR variant that combines iterative solution construction with gradient ...
متن کاملAvoiding Local Optima in Single Particle Reconstruction
In single-particle reconstruction, a 3D structure is reconstructed from a large number of randomly oriented 2D projections, using techniques related to computed tomography. Unlike in computed tomography, however, the orientations of the projections must be estimated at the same time as the 3D structure, and hence the reconstruction process can be error-prone, converging to an incorrect local op...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Multivariate Behavioral Research
سال: 2016
ISSN: 0027-3171,1532-7906
DOI: 10.1080/00273171.2016.1160359