搜索结果: 1-12 共查到“Random projections”相关记录12条 . 查询时间(0.093 秒)
Margin-constrained Random Projections And Very Sparse Random Projections
Random Projections Sampling Maximum Likelihood Asymptotic Analysis
2015/8/21
We propose methods for improving both the accuracy and efficiency of random projections, the popular dimension reduction technique in machine learning and data mining, particularly useful for estimati...
Improving Random Projections Using Marginal Information
Random Projections Marginal Information
2015/8/21
We present an improved version of random projections that takes advantage of marginal norms. Using a maximum likelihood estimator (MLE), marginconstrained random projections can improve estimation acc...
There has been considerable interest in random projections, an approximate algorithm for estimating distances between pairs of points in a high-dimensional vector space. Let A ∈ Rn×D be our n points i...
A Unified Near-Optimal Estimator For Dimension Reduction in lα (0 < α ≤ 2) Using Stable Random Projections
Near-Optimal Estimator Dimension Reduction Stable Random Projections
2015/8/21
Many tasks (e.g., clustering) in machine learning only require the lα distances instead of the original data. For dimension reductions in the lα norm (0 < α ≤ 2), the method of stable random projectio...
Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections
dimension reduction l1 norm Johnson-Lindenstrauss (JL) lemma Cauchy random projections
2015/8/21
For1 dimension reduction in the l1 norm, the method of Cauchy random projections multiplies the original data matrix A ∈ Rn×D with a random matrix R ∈ RD×k (k D) whose entries are i.i.d. samples of ...
Near Optimal Signal Recovery From Random Projections:Universal Encoding Strategies?
Random matrices singular values of random matrices signal recovery random projections concentration of measure sparsity trigonometric expansions uncertainty principle convex optimization duality in optimization linear programming
2015/6/17
Suppose we are given a vector f in a class F ⊂ RN, e.g. a class of digital signals or digital images. How many linear measurements do we need to make about f to be able to recover f to within pr...
Can we recover a signal f ∈ RN from a small number of linear measurements? A series of recent papers developed a collection of results showing that it is surprisingly possible to reconstruct certain t...
Random Projections, Graph Sparsification, and Differential Privacy
Differential Privacy Graph sparsification
2014/3/10
This paper initiates the study of preserving {\em differential privacy} ({\sf DP}) when the data-set is sparse. We study the problem of constructing efficient sanitizer that preserves {\sf DP} and gua...
Topic Discovery through Data Dependent and Random Projections
Topic Discovery through Data Dependent and Random Projections
2013/4/27
We present algorithms for topic modeling based on the geometry of cross-document word-frequency patterns. This perspective gains significance under the so called separability condition. This is a cond...
Resistant estimates for high dimensional and functional data based on random projections
Resistant estimates high dimensional functional data based
2011/7/5
In this paper we propose a new robust estimation method based on random projections which is adaptive, produces an automatic robust estimate, while being easy to compute for high or infinite dimension...
Semigroups of finite-dimensional random projections
Stochastic semigroup random operator Kolmogorov widths stochastic flow
2010/12/9
In this paper we present a complete description of a stochastic semigroup of finite-dimensional projections in Hilbert space. The geometry of such semigroups is characterized by the asymptotic be-havi...
Fast global image registration using random projections
image registration global optimization random projections
2009/12/23
Fast global image registration using random projections.