In this chapter, we discuss a problem of estimation of a large target matrix based 4 on a finite number of noisy measurements of linear functionals (often, random) 5 of this matrix. The underlying assumption is that the target matrix is of small 6 rank and the goal is to determine how ...
Low-rank matrix recovery problem is difficult due to its non-convex properties and it is usually solved using convex relaxation approaches. In this paper, we formulate the non-convex low-rank matrix recovery problem exactly using novel Ky Fan 2-k-norm-based models. A general difference of conv...
We design a new distribution over $\poly(r \eps^{-1}) imes n$ matrices $S$ so that for any fixed $n imes d$ matrix $A$ of rank $r$, with probability at least 9/10, $orm{SAx}_2 = (1 \pm \eps)orm{Ax}_2$ simultaneously for all $x \in \mathbb{R}^d$. Such a matrix...
推荐系统(recommender systems):预测电影评分--构造推荐系统的一种方法:低秩矩阵分解(low rank matrix factorization) 3031 如上图中的predicted ratings矩阵可以分解成X与ΘT的乘积,这个叫做低秩矩阵分解。 我们先学习出product的特征参数向量,在实际应用中这些学习出来的参数向量可能比较难以理解,也很难可视化出来,但是它...
Low-Rank Representation refers to a minimization problem that involves fitting a given data matrix to an approximating matrix with a low rank, aiming to detect outliers and decompose the data into low-rank and sparse components. AI generated definition based on: Computer Science Review, 2017 ...
deep-neural-networkssparsityaccelerationcompressioncaffelow-rank-approximationsparse-convolution UpdatedMar 8, 2020 C++ je-suis-tm/machine-learning Star168 Code Issues Pull requests Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm imp...
rank minimization based one, the alternating direction method of multipliers (ADMM) algorithm is employed. At each iteration, rather than computing singular value decomposition (SVD) of all the mode-kunfolding matrices as it does in many tensor regression based on other decomposition methods [23],...
LRA (redirected fromLow Rank Approximation) Category filter: AcronymDefinition LRALord's Resistance Army(rebel group in Uganda) LRALouisiana Recovery Authority LRALabour Relations Act(various locations) LRALocal Redevelopment Authority(Section 2910, Defense Base Closure and Realignment Act of 1990, as ame...
Keywords Rank minimization · Ky Fan 2-k-norm · Matrix recovery 1 Introduction Matrix recovery problem concerns the construction of a matrix from incomplete information of its entries. This problem has a wide range of applications such as recommendation systems with incomplete information of users' ...
The explosive growth of data has caused users to spend considerable time and effort finding the items they need. Various recommender systems have been crea