Description: Builds a nearest neighbor graph in a very short time.In many cases is faster than ANN library. Platform: |
Size: 14336 |
Author:Sama |
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Description: In graph theory, breadth-first search (BFS) is a graph search algorithm that begins at the root node and explores all the neighboring nodes. Then for each of those nearest nodes, it explores their unexplored neighbor nodes, and so on, until it finds the goal. Platform: |
Size: 1024 |
Author:a32 |
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Description: 关于metric learning的综述，涉及到许多的知识：SVM、kernel、SDP等-This paper surveys the field of distance
metric learning from a principle perspective, and includes a broad selection of recent work. In particular, distance metric learning is reviewed under different
learning conditions: supervised learning versus unsupervised learning, learning in a global sense versus in a local sense and the distance matrix based on linear kernel versus nonlinear kernel. In addition, this paper discusses a number of techniques
that is central to distance metric learning, including convex programming, positive semi-definite programming, kernel learning, dimension reduction, K Nearest Neighbor, large margin classification, and graph-based approaches. Platform: |
Size: 322560 |
Author:刘建飞 |
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Description: In the proposed algorithm, these two issues are solved by a novel predicate, which is defined by the sequential probability ratio test (SPRT) and the minimal cost criterion. Starting from an over-segmented image, neighboring regions are progressively merged if there is an evidence for merging according to this predicate. We show that the merging order follows the principle of dynamic programming. This formulates image segmentation as an inference problem, where the final segmentation is established based on the observed image. We also prove that the produced segmentation satisfies certain global properties. In addition, a faster algorithm is developed to accelerate the region merging process, which maintains a nearest neighbor graph (NNG) in each iteration. Platform: |
Size: 59392 |
Author:michael |
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Description: its a machine learning programme which uses k nearest neighbor algorithm, find the distances between the k features point and plots the graph. Platform: |
Size: 1024 |
Author:Anup Sah |
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Description: D MANUSC
Graph-optimized Locality Preserving Projections (GoLPP) algorithm [28]. GoLPP
integrated the graph construction and a specific dimensionality reduction process (i.e.
LPP) into a unified framework, which results in a simultaneous learning for optimal
graph and projection matrix. From the experimental results in [20], it was demonstrated
that the GoLPP outperformed the classical LPP which is based on k nearest neighbor -
Graph-optimized Locality Preserving Projections (GoLPP) algorithm [28]. GoLPP
integrated the graph construction and a specific dimensionality reduction process (i.e.
LPP) into a unified framework, which results in a simultaneous learning for optimal
graph and projection matrix. From the experimental results in [20], it was demonstrated
that the GoLPP outperformed the classical LPP which is based on k nearest neighbor Platform: |
Size: 1024 |
Author:骕骦 |
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Description: 本书示例丰富，图文并茂，以让人容易理解的方式阐释了算法，旨在帮助程序员在日常项目中更好地发挥算法的能量。书中的前三章将帮助你打下基础，带你学习二分查找、大O表示法、两种基本的数据结构以及递归等。余下的篇幅将主要介绍应用广泛的算法，具体内容包括：面对具体问题时的解决技巧，比如，何时采用贪婪算法或动态规划；散列表的应用；图算法；K最近邻算法(This book is rich in examples, illustrations, and explains the algorithm in an easy-to-understand way designed to help programmers better harness the power of algorithms in their everyday projects. The first three chapters in the book will help you lay the groundwork, take you to the study of binary search, large O notation, two basic data structures, and recursion. The rest of this section will cover the most widely used algorithms, including: How to solve face-to-face problems, such as when to use greedy algorithms or dynamic programming; Hashtable applications; Graph algorithms; K nearest neighbor algorithms) Platform: |
Size: 16652288 |
Author:WFDDDYS |
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Description: 本书示例丰富,图文并茂,以简明易懂的方式阐释了算法,旨在帮助程序员在日常项目中更好地利用 算法为软件开发助力。前三章介绍算法基础,包括二分查找、大 O 表示法、两种基本的数据结构以及递归 等。余下的篇幅将主要介绍应用广泛的算法,具体内容包括 :面对具体问题时的解决技巧,比如何时采用 贪婪算法或动态规划 ;散列表的应用 ;图算法 ;K 最近邻算法。
本书适合所有程序员、计算机专业相关师生以及对算法感兴趣的读者(This book is rich in examples and illustrates algorithms in a concise and easy-to-understand way. It aims to help programmers make better use of algorithms in daily projects to help software development. The first three chapters introduce the basic algorithms, including binary search, large O representation, two basic data structures and recursion. The rest of the paper will focus on the widely used algorithms, including: when to use greedy algorithm or dynamic programming, hash table application, graph algorithm, K nearest neighbor algorithm when facing specific problems.
This book is suitable for all programmers, computer-related teachers and students, and readers interested in algorithms.) Platform: |
Size: 16691200 |
Author:辉-triste |
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Search - Nearest Neighbor graph