Identification model based on latent variables
نویسندگان
چکیده
منابع مشابه
mortality forecasting based on lee-carter model
over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...
15 صفحه اولDeep Part-Based Generative Shape Model with Latent Variables
The Shape Boltzmann Machine (SBM) [6] and its multilabel version MSBM [5] have been recently introduced as deep generative models that capture the variations of an object shape. While being more flexible MSBM requires datasets with labeled parts of the objects for training. In the paper we present an algorithm for training MSBM using binary masks of objects and the seeds which approximately cor...
متن کاملModel Selection in a Settingwith Latent Variables
Model selection, the task of selecting a statistical model from a certain model class given data, is an important problem in statistical learning. From another perspective model selection can also be viewed as learning a single distribution, where the parameter space includes a discrete structure parameter s which imposes further constraints on the remaining parameterization of that model, so t...
متن کاملQuartet-Based Learning of Shallow Latent Variables
Hierarchical latent class(HLC) models are tree-structured Bayesian networks where leaf nodes are observed while internal nodes are hidden. We explore the following two-stage approach for learning HLC models: One first identifies the shallow latent variables – latent variables adjacent to observed variables – and then determines the structure among the shallow and possibly some other “deep” late...
متن کاملHMM Analysis of Musical Structure: Identification of Latent Variables Through Topology-Sensitive Model Selection
Hiden Markov Models (HMMs) have been successfully employed in the exploration and modeling of musical structure, with applications in Music Information Retrieval. This paper focuses on an aspect of HMM training that remains relatively unexplored in musical applications, namely the determination of HMM topology. We demonstrate that this complex problem can be effectively addressed through search...
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: Journal of Physics: Conference Series
سال: 2020
ISSN: 1742-6588,1742-6596
DOI: 10.1088/1742-6596/1679/5/052029