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Approximation algorithms for maximally balanced connected graph partition
Given a connected graph G=(V, E) G=(V, E), we seek to partition the vertex set V into k non-
empty parts such that the subgraph induced by each part is connected, and the partition is …
empty parts such that the subgraph induced by each part is connected, and the partition is …
Graph clustering-based discretization of splitting and merging methods (graphs and graphm)
Discretization plays a major role as a data preprocessing technique used in machine
learning and data mining. Recent studies have focused on multivariate discretization that …
learning and data mining. Recent studies have focused on multivariate discretization that …
Partitioning a graph into connected components with fixed centers and optimizing cost‐based objective functions or equipartition criteria
We consider a connected graph G with n vertices, p of which are centers, while the
remaining ones are units. For each unit‐center pair, there is a fixed assignment cost and for …
remaining ones are units. For each unit‐center pair, there is a fixed assignment cost and for …
Double-fold localized multiple matrix learning machine with Universum
C Zhu - Pattern Analysis and Applications, 2017 - Springer
Matrix learning, multiple-view learning, Universum learning, and local learning are four hot
spots of present research. Matrix learning aims to design feasible machines to process …
spots of present research. Matrix learning aims to design feasible machines to process …
Breast epithelial duct region segmentation using intuitionistic fuzzy based multi-texture image map
Currently histology breast cancer tissue interpretation through microscope is a manual
procedure. Inter-intra-observer variability in breast cancer diagnosis by expert pathologist …
procedure. Inter-intra-observer variability in breast cancer diagnosis by expert pathologist …
[HTML][HTML] Uniform and most uniform partitions of trees
This paper addresses centered and non centered equipartition tree problems into p
connected components (p-partitions). In the former case, each partition must contain exactly …
connected components (p-partitions). In the former case, each partition must contain exactly …
Single-image motion deblurring using an adaptive image prior
Blind deblurring is the restoration of a sharp image from a blurred image when the blur
kernel is unknown. Most image deblurring algorithms impose a uniform sparse gradient prior …
kernel is unknown. Most image deblurring algorithms impose a uniform sparse gradient prior …
Double-fold localized multiple matrixized learning machine
In this paper, we develop an effective multiple-matrixized learning machine named Double-
fold Localized Multiple Matrixized Learning Machine (DLMMLM). The characteristic of the …
fold Localized Multiple Matrixized Learning Machine (DLMMLM). The characteristic of the …
[PDF][PDF] 基于 Universum 学
朱昌明， 吴爱华， 王健安 - 上海海事 大学 学报 - containerizations.com
为解决原始核聚类(Kernel Clustering, KC) 中模式信息不足, 聚类结果不佳的缺点, 以KC 为基础,
利用Universum 学**带来的优势, 提出基于Universum 学**的核聚类(Universum learning …
利用Universum 学**带来的优势, 提出基于Universum 学**的核聚类(Universum learning …
基于 Universum 学**的核聚类方法
朱昌明， 吴爱华， 王健安 - 上海海事大学学报, 2016 - containerizations.com
为解决原始核聚类(Kernel Clustering, KC) 中模式信息不足, 聚类结果不佳的缺点, 以KC 为基础,
利用Universum 学**带来的优势, 提出基于Universum 学**的核聚类(Universum …
利用Universum 学**带来的优势, 提出基于Universum 学**的核聚类(Universum …