Uses of Class
org.apache.sysds.hops.estim.SparsityEstimator

Packages that use SparsityEstimator
Package
Description
 
  • Uses of SparsityEstimator in org.apache.sysds.hops.estim

    Modifier and Type
    Class
    Description
    class 
    Basic average case estimator for matrix sparsity: sp = 1 - Math.pow(1-sp1*sp2, k)
    class 
    Basic average case estimator for matrix sparsity: sp = Math.min(1, sp1 * k) * Math.min(1, sp2 * k).
    class 
    This estimator implements a naive but rather common approach of boolean matrix multiplies which allows to infer the exact non-zero structure and thus is also useful for sparse result preallocation.
    class 
    This estimator implements an approach called density maps, as introduced in David Kernert, Frank Köhler, Wolfgang Lehner: SpMacho - Optimizing Sparse Linear Algebra Expressions with Probabilistic Density Estimation.
    class 
    This estimator implements an approach based on a so-called layered graph, introduced in Edith Cohen.
    class 
    This estimator implements a remarkably simple yet effective approach for incorporating structural properties into sparsity estimation.
    class 
    This estimator implements an approach based on row-wise sparsity estimation, introduced in Lin, Chunxu, Wensheng Luo, Yixiang Fang, Chenhao Ma, Xilin Liu and Yuchi Ma: On Efficient Large Sparse Matrix Chain Multiplication.
    class 
    This estimator implements an approach based on row/column sampling Yongyang Yu, MingJie Tang, Walid G.
    class 
    This estimator implements an approach based on row/column sampling Rasmus Resen Amossen, Andrea Campagna, Rasmus Pagh: Better Size Estimation for Sparse Matrix Products.