Data-Free/Data-Sparse Softmax Parameter Estimation With Structured Class Geometries
نویسندگان
چکیده
منابع مشابه
Sparse Estimation with Structured Dictionaries
In the vast majority of recent work on sparse estimation algorithms, performance has been evaluated using ideal or quasi-ideal dictionaries (e.g., random Gaussian or Fourier) characterized by unit l2 norm, incoherent columns or features. But in reality, these types of dictionaries represent only a subset of the dictionaries that are actually used in practice (largely restricted to idealized com...
متن کاملPolar Operators for Structured Sparse Estimation
Structured sparse estimation has become an important technique in many areas of data analysis. Unfortunately, these estimators normally create computational difficulties that entail sophisticated algorithms. Our first contribution is to uncover a rich class of structured sparse regularizers whose polar operator can be evaluated efficiently. With such an operator, a simple conditional gradient m...
متن کاملChange Point Detection by Sparse Parameter Estimation
The contribution is focused on change point detection in a one-dimensional stochastic process by sparse parameter estimation from an overparametrized model. A stochastic process with change in the mean is estimated using dictionary consisting of Heaviside functions. The basis pursuit algorithm is used to get sparse parameter estimates. The mentioned method of change point detection in a stochas...
متن کاملSparse Nonlinear Regression: Parameter Estimation under Nonconvexity
We study parameter estimation for sparse nonlinear regression. More specifically, we assume the data are given by y = f(x�β∗) + �, where f is nonlinear. To recover β∗, we propose an �1regularized least-squares estimator. Unlike classical linear regression, the corresponding optimization problem is nonconvex because of the nonlinearity of f . In spite of the nonconvexity, we prove that under mil...
متن کاملUsing Sparse Parameter Estimation for Semantic Parsing
This paper addresses the problem of semantic parsing, by which natural language sentences are translated into a form which conveys their underlying meaning. Semantic parsing involves a parameter estimation process, which is a convex optimization problem. The optimization formulation of previous approaches often requires huge amount of time to converge due to the high dimensional feature space. ...
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 Signal Processing Letters
سال: 2018
ISSN: 1070-9908,1558-2361
DOI: 10.1109/lsp.2018.2860238