Efficient Recognition of Totally Nonnegative Matrix Cells

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Efficient Recognition of Totally Nonnegative Matrix Cells

The space of m × p totally nonnegative real matrices has a stratification into totally nonnegative cells. The largest such cell is the space of totally positive matrices. There is a well-known criterion due to Gasca and Peña for testing a real matrix for total positivity. This criterion involves testing mp minors. In contrast, there is no known small set of minors for testing for total nonnegat...

متن کامل

Totally nonnegative cells and matrix Poisson varieties

We describe explicitly the admissible families of minors for the totally nonnegative cells of real matrices, that is, the families of minors that produce nonempty cells in the cell decompositions of spaces of totally nonnegative matrices introduced by A. Postnikov. In order to do this, we relate the totally nonnegative cells to torus orbits of symplectic leaves of the Poisson varieties of compl...

متن کامل

Efficient Nonnegative Matrix Factorization with Random Projections

The recent years have witnessed a surge of interests in Nonnegative Matrix Factorization (NMF) in data mining and machine learning fields. Despite its elegant theory and empirical success, one of the limitations of NMF based algorithms is that it needs to store the whole data matrix in the entire process, which requires expensive storage and computation costs when the data set is large and high...

متن کامل

Incremental Nonnegative Matrix Factorization for Face Recognition

Nonnegative matrix factorization NMF is a promising approach for local feature extraction in face recognition tasks. However, there are two major drawbacks in almost all existing NMFbased methods. One shortcoming is that the computational cost is expensive for large matrix decomposition. The other is that it must conduct repetitive learning, when the training samples or classes are updated. To ...

متن کامل

Character Recognition Analysis with Nonnegative Matrix Factorization

In this paper, we analyze character recognition performance of three different nonnegative matrix factorization (NMF) algorithms. These are multiplicative update (MU) rule known as standard NMF, alternating least square (NMF-ALS) and projected gradient descent (NMF-PGD). They are most preferred approaches in the literature. There are lots of application areas for NMF such as robotics, bioinform...

متن کامل

ذخیره 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: Foundations of Computational Mathematics

سال: 2013

ISSN: 1615-3375,1615-3383

DOI: 10.1007/s10208-013-9169-5