Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion
نویسندگان
چکیده
منابع مشابه
Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion
In this paper, we propose an efficient and scalable low rank matrix completion algorithm. The key idea is to extend orthogonal matching pursuit method from the vector case to the matrix case. We further propose an economic version of our algorithm by introducing a novel weight updating rule to reduce the time and storage complexity. Both versions are computationally inexpensive for each matrix ...
متن کاملOrthogonal Rank-One Matrix Pursuit for Matrix Completion
Low rank modeling has found applications in a wide range of machine learning and data mining tasks, such as matrix completion, dimensionality reduction, compressed sensing, multi-class and multi-task learning. Recently, significant efforts have been devoted to the low rank matrix completion problem, as it has important applications in many domains including collaborative filtering, Microarray d...
متن کاملRank-One Matrix Pursuit for Matrix Completion
Low rank matrix completion has been applied successfully in a wide range of machine learning applications, such as collaborative filtering, image inpainting and Microarray data imputation. However, many existing algorithms are not scalable to large-scale problems, as they involve computing singular value decomposition. In this paper, we present an efficient and scalable algorithm for matrix com...
متن کاملLow-Rank Matrix Completion
While datasets are frequently represented as matrices, real-word data is imperfect and entries are often missing. In many cases, the data are very sparse and the matrix must be filled in before any subsequent work can be done. This optimization problem, known as matrix completion, can be made well-defined by assuming the matrix to be low rank. The resulting rank-minimization problem is NP-hard,...
متن کاملDecomposition Approach for Low-rank Matrix Completion
In this paper, we describe a low-rank matrix completion method based on matrix decomposition. An incomplete matrix is decomposed into submatrices which are filled with a proposed trimming step and then are recombined to form a low-rank completed matrix. The divide-and-conquer approach can significantly reduce computation complexity and storage requirement. Moreover, the proposed decomposition m...
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: SIAM Journal on Scientific Computing
سال: 2015
ISSN: 1064-8275,1095-7197
DOI: 10.1137/130934271