搜索结果: 1-15 共查到“管理学 Metric”相关记录15条 . 查询时间(0.078 秒)
Metric Selection in Fast Dual Forward Backward Splitting
Metric Selection Fast Dual Forward Backward Splitting
2015/7/9
The performance of fast forward-backward splitting, or equivalently fast proximal gradient methods, is susceptible to conditioning of the optimization problem data. This conditioning is related to a m...
Non-linear dimensionality reduction: Riemannian metric estimation and the problem of geometric discovery
Non-linear dimensionality reduction Riemannian metric estimation the problem geometric discovery
2013/6/14
In recent years, manifold learning has become increasingly popular as a tool for performing non-linear dimensionality reduction. This has led to the development of numerous algorithms of varying degre...
Statistical Analysis of Metric Graph Reconstruction
Metric Graph Filament Reconstruction Manifold Learning Minimax Esti-mation
2013/6/13
A metric graph is a 1-dimensional stratified metric space consisting of vertices and edges or loops glued together. Metric graphs can be naturally used to represent and model data that take the form o...
Relevance As a Metric for Evaluating Machine Learning Algorithms
Machine learning algorithms performance metric proba-bilistic approach
2013/4/28
In machine learning, the choice of a learning algorithm that is suitable for the application domain is critical. The performance metric used to compare different algorithms must also reflect the conce...
Large-Margin Metric Learning for Partitioning Problems
Large-Margin Metric Learning Partitioning Problems
2013/4/28
In this paper, we consider unsupervised partitioning problems, such as clustering, image segmentation, video segmentation and other change-point detection problems. We focus on partitioning problems b...
Distance Metric Learning for Kernel Machines
metric learning distance learning support vector machines semi-de nite programming Mahalanobis distance
2012/9/17
Recent work in metric learning has signi cantly improved the state-of-the-art ink-nearest neighbor classi cation. Support vector machines (SVM), particularly with RBF kernels, are amongst the most pop...
Metric distances derived from cosine similarity and Pearson and Spearman correlations
Metric distances derived cosine similarity Pearson and Spearman correlations
2012/9/17
We investigate two classes of transformations of cosine similarity and Pearson and Spearman correlations into metric distances, utilising the simple tool of metric-preserving functions. The rst class...
Fast, Linear Time Hierarchical Clustering using the Baire Metric
Fast Linear Time Hierarchical Clustering using Baire Metric
2011/7/5
The Baire metric induces an ultrametric on a dataset and is of linear computational complexity, contrasted with the standard quadratic time agglomerative hierarchical clustering algorithm.
A metric system for feature and cost control during product development
product development quality metrics toy industry
2009/12/1
The use of metrics to control the product development process (PDP) in real time
poses a challenge for product development research. To date, control has been limited to the final
phase of the proje...
Mathematical expectation and martingales of random subsets of a metric space
Mathematical expectation martingales of random subsets a metric space
2009/9/23
Mathematical expectation and martingales of random subsets of a metric space。
Mathematical expectation and Strong Law of Large Numbers for random variables with values in a metric space of negative curvature
Mathematical expectation Strong Law of Large Numbers random variables
2009/9/23
Let f be a random variable with values in a metric
space (X, d). For some class of metric spaces we define in terms of the
metric d mathematical expectation of f as a closed bounded and
non-empty s...
METRIC ENTROPY AND THE SMALL DEVIATION PROBLEM FOR STABLE PROCESSES
Small deviation lower tail probability Gaussian processes stable processes metric entropy
2009/9/18
The famous connection between metric entropy and
small deviation probabilities of Gaussian processes was discovered by
Kuelbs and Li in [6] and completed by Li and Linde in [9]. The
question whethe...
We define and build H-fractional α-stable fields indexed by a metric space (E,d). We mainly apply these results to spheres, hyperbolic spaces and real trees.
We define and build H-fractional α-stable fields indexed by a metric space (E,d). We mainly apply these results to spheres, hyperbolic spaces and real trees
Metric Embedding for Nearest Neighbor Classification
Metric Embedding Nearest Neighbor Classification
2010/4/29
The distance metric plays an important role in nearest neighbor (NN) classification. Usually
the Euclidean distance metric is assumed or a Mahalanobis distance metric is optimized
to improve the NN ...