Simultaneous Bayesian Sparse Approximation With Structured Sparse Models
نویسندگان
چکیده
منابع مشابه
Structured Sparse Additive Models
1.1 Parametric models: Linear Regression with non-linear basis functions Although the linear regression with linear basis is widely used in different areas, it is not powerful enough for lots of the real world cases as not all the models are linear in the real world. However, we can use non-linear basis functions to deal with non-linear relationships. It is just a linear combination of some fun...
متن کاملBayesian Models for Structured Sparse Estimation via Set Cover Prior
A number of priors have been recently developed for Bayesian estimation of sparse models. In many applications the variables are simultaneously relevant or irrelevant in groups, and appropriately modeling this correlation is important for improved sample efficiency. Although group sparse priors are also available, most of them are either limited to disjoint groups, or do not infer sparsity at g...
متن کاملRobust Estimation in Linear Regression with Molticollinearity and Sparse Models
One of the factors affecting the statistical analysis of the data is the presence of outliers. The methods which are not affected by the outliers are called robust methods. Robust regression methods are robust estimation methods of regression model parameters in the presence of outliers. Besides outliers, the linear dependency of regressor variables, which is called multicollinearity...
متن کاملFast Laplace Approximation for Sparse Bayesian Spike and Slab Models
We consider the application of Bayesian spike-andslab models in high-dimensional feature selection problems. To do so, we propose a simple yet effective fast approximate Bayesian inference algorithm based on Laplace’s method. We exploit two efficient optimization methods, GIST [Gong et al., 2013] and L-BFGS [Nocedal, 1980], to obtain the mode of the posterior distribution. Then we propose an en...
متن کاملLearning Efficient Structured Sparse Models
We present a comprehensive framework for structured sparse coding and modeling extending the recent ideas of using learnable fast regressors to approximate exact sparse codes. For this purpose, we propose an efficient feed forward architecture derived from the iteration of the block-coordinate algorithm. This architecture approximates the exact structured sparse codes with a fraction of the com...
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: IEEE Transactions on Signal Processing
سال: 2016
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2016.2605067