منابع مشابه
Correntropy Based Matrix Completion
This paper studies the matrix completion problems when the entries are contaminated by non-Gaussian noise or outliers. The proposed approach employs a nonconvex loss function induced by the maximum correntropy criterion. With the help of this loss function, we develop a rank constrained, as well as a nuclear norm regularized model, which is resistant to non-Gaussian noise and outliers. However,...
متن کاملDocument Clustering Based On Max-Correntropy Non-Negative Matrix Factorization
Nonnegative matrix factorization (NMF) has been successfully applied to many areas for classification and clustering. Commonly-used NMF algorithms mainly target on minimizing the l2 distance or Kullback-Leibler (KL) divergence, which may not be suitable for nonlinear case. In this paper, we propose a new decomposition method by maximizing the correntropy between the original and the product of ...
متن کاملGraph Matrix Completion in Presence of Outliers
Matrix completion problem has gathered a lot of attention in recent years. In the matrix completion problem, the goal is to recover a low-rank matrix from a subset of its entries. The graph matrix completion was introduced based on the fact that the relation between rows (or columns) of a matrix can be modeled as a graph structure. The graph matrix completion problem is formulated by adding the...
متن کاملNGS Based Haplotype Assembly Using Matrix Completion
We use matrix completion methods for haplotype assembly from NGS reads to develop the new HapSVT, HapNuc, and HapOPT algorithms. This is performed by applying a mathematical model to convert the reads to an incomplete matrix and estimating unknown components. This is followed by quantizing and decoding the completed matrix in order to generate haplotypes. These algorithms are compared to the re...
متن کاملSequential Matrix Completion
We propose a novel algorithm for sequential matrix completion in a recommender system setting, where the (i, j)th entry of the matrix corresponds to a user i’s rating of product j. The objective of the algorithm is to provide a sequential policy for user-product pair recommendation which will yield the highest possible ratings after a finite time horizon. The algorithm uses a Gamma process fact...
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: Entropy
سال: 2018
ISSN: 1099-4300
DOI: 10.3390/e20030171