Alternating Group Lasso for Block-Term Tensor Decomposition and Application to ECG Source Separation
نویسندگان
چکیده
منابع مشابه
Block-Decoupling Multivariate Polynomials Using the Tensor Block-Term Decomposition
We present a tensor-based method to decompose a given set of multivariate functions into linear combinations of a set of multivariate functions of linear forms of the input variables. The method proceeds by forming a three-way array (tensor) by stacking Jacobian matrix evaluations of the function behind each other. It is shown that a blockterm decomposition of this tensor provides the necessary...
متن کاملBlock-sparse Solutions using Kernel Block RIP and its Application to Group Lasso
We propose kernel block restricted isometry property (KB-RIP) as a generalization of the well-studied RIP and prove a variety of results. First, we present a “sumof-norms”-minimization based formulation of the sparse recovery problem and prove that under suitable conditions on KB-RIP, it recovers the optimal sparse solution exactly. The Group Lasso formulation, widely used as a good heuristic, ...
متن کاملLearning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition
Recurrent Neural Networks (RNNs) are powerful sequence modeling tools. However, when dealing with high dimensional inputs, the training of RNNs becomes computational expensive due to the large number of model parameters. This hinders RNNs from solving many important computer vision tasks, such as Action Recognition in Videos and Image Captioning. To overcome this problem, we propose a compact a...
متن کاملAn Efficient Algorithm to Estimate Mixture Matrix in Blind Source Separation using Tensor Decomposition
The estimation of mixing matrix is a key step to solve the problem of blind source separation. The existing algorithm can only estimate the matrix of well-determined, over-determined and under-determined in condition of sparse source. Scaling and permutation ambiguities lie in both factor matrix of tensor Canonical Decomposition and mixing matrix in blind source separation. With this property, ...
متن کاملEfficient block-coordinate descent algorithms for the Group Lasso
We present two algorithms to solve the Group Lasso problem [33]. First, we propose a general version of the Block Coordinate Descent (BCD) algorithm for the Group Lasso that employs an efficient approach for optimizing each subproblem exactly. We show that it exhibits excellent performance when the groups are of moderate size. For groups of large size, we propose an extension of ISTA/FISTA [2] ...
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: 2020
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2020.2985591