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Colored intersection searching via sparse rectangular matrix multiplication

2006
*
Proceedings of the twenty-second annual symposium on Computational geometry - SCG '06
*

In a

doi:10.1145/1137856.1137866
dblp:conf/compgeom/KaplanSV06
fatcat:b4aihjoo2jcupnljgsuc2zfgly
*Sparse**Rectangular**Matrix**Multiplication*Problem (SRM M ), one is given an n1 × n2*matrix*A and an n2 × n3*matrix*B, each containing at most m non-zero entries, and the goal is to compute their product ... Finally, use an algorithm for*sparse**matrix**multiplication*(adapted from Yuster and Zwick [20]) to compute the union of the bicliques. ...*Sparse**rectangular**matrix**multiplication*. ...##
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Monochromatic Triangles, Triangle Listing and APSP
[article]

2020
*
arXiv
*
pre-print

It is equivalent to the problem of listing m triangles in an m-edge graph where m=Õ(n^1.5), and can be solved in O(m^1.41) time [Alon et al.'97] with the current

arXiv:2007.09318v2
fatcat:m56kcys2x5ftxlewesp3csv6xa
*matrix**multiplication*bounds, and in Õ( ...*Via*work of [Lincoln et al.'20], our result on All-Edges*Sparse*Triangle implies that if the All-Edges Monochromatic Triangle problem has an O(n^2.5-ϵ) time algorithm for ϵ>0, then both the APSP and 3SUM ... We will use*colors*on the edges to perform parallel binary*search*to find the (min, =)-product. ...##
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Multiple kernel learning from sets of partially matching image features

2008
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Pattern Recognition (ICPR), Proceedings of the International Conference on
*

We demonstrate our algorithm on classification tasks, including object recognition and classification, which is based on a linear combination of histogram

doi:10.1109/icpr.2008.4761342
dblp:conf/icpr/FuSHLT08
fatcat:dnd4jik7abcyfedqhcuxlh2tli
*intersection*kernels, computed at*multiple*pyramid ... Weights on each kernel*matrix*(level) are included in the standard SVM empirical risk minimization problem with a L 2 constraint to encourage sparsity. ... (This figure is best viewed in*color*.) bins corresponding to the sparsity of the features obtained above, for the dense distributed part, we set more bins there, while for the*sparsed*region, the number ...##
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Local Feature Design Concepts, Classification, and Learning
[chapter]

2014
*
Computer Vision Metrics
*

For

doi:10.1007/978-1-4302-5930-5_4
fatcat:va2d2tylszhu7h3uefu54s76a4
*sparse*local features, the*search*strategy becomes important. ...*Sparse*Predictive*Search*and Tracking In a*sparse*predictive*search*pipeline, specific features at known locations, found in previous frames, are*searched*for in the next frame at the expected positions ...##
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Exploiting Multiple Levels of Parallelism in Sparse Matrix-Matrix Multiplication

2016
*
SIAM Journal on Scientific Computing
*

*Sparse*

*matrix*-

*matrix*

*multiplication*(or SpGEMM) is a key primitive for many high-performance graph algorithms as well as for some linear solvers, such as algebraic multigrid. ... In this work, we present the first ever implementation of the 3D SpGEMM formulation that also exploits

*multiple*(intra-node and inter-node) levels of parallelism, achieving significant speedups over the ... They show that this approach would incur less memory traffic than performing

*sparse*inner products by a factor of n/n

*color*where n

*color*is the number of

*colors*used for

*matrix*

*coloring*. ...

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Sparse Representation of Deformable 3D Organs with Spherical Harmonics and Structured Dictionary

2011
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International Journal of Biomedical Imaging
*

All results demonstrated that the proposed algorithm features

doi:10.1155/2011/658930
pmid:21941524
pmcid:PMC3175754
fatcat:6qzmqfkpqbfzdcvgtizo3fa3tu
*sparse*representation of deformable surfaces with low dimensionality and high accuracy. ... This paper proposed a novel algorithm to*sparsely*represent a deformable surface (SRDS) with low dimensionality based on spherical harmonic decomposition (SHD) and orthogonal subspace pursuit (OSP). ... Figure 4 :Figure 5 :Figure 6 : 456 Ray casting sampling: (a) unique ray-surface*intersection*, (b)*multiple*ray-surface*intersections*, and (c) ray casting on two deformed surfaces. ...##
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A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification

2016
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Remote Sensing
*

One branch of research combines

doi:10.3390/rs8030259
fatcat:7kvdas6kkjacnjighi3patijtq
*multiple*complementary features based on various aspects such as texture,*color*and structure. ... In this paper, we propose combining the two methods under a tree of regions and present a new descriptor to encode*color*, texture and structure features using a hierarchical structure-*Color*Binary Partition ... Figure 3 . 3 The segmentation of the HRS image*via**Color*Binary Partition Tree (CBPT) (a) An HRS airport image; (b) Segmentation results at*multiple*scales. ...##
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OnSet: A Visualization Technique for Large-scale Binary Set Data

2014
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IEEE Transactions on Visualization and Computer Graphics
*

Each set is represented as a

doi:10.1109/tvcg.2014.2346249
pmid:26356913
fatcat:z574pz4fabdgddngc6bpi5p5pi
*rectangular*region with the set elements being smaller interior rectangles. ... This work was supported by the Georgia Aquarium, the DARPA XDATA program, and the National Science Foundation*via*awards CCF-0808863 (FODAVA) and IIS-1320537. ... Note, however, that one of these pixels in OnSet is likely implemented by a*rectangular*region of*multiple*, actual screen pixels. ...##
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Interest Point Detector and Feature Descriptor Survey
[chapter]

2014
*
Computer Vision Metrics
*

RFM2.3 Summary Taxonomy Spectra: Normalized histogram patch intensity encoded into binary patch index code Feature shape:

doi:10.1007/978-1-4302-5930-5_6
fatcat:3jmbq6bpivfqxaq7mcwbs5t2yy
*Rectangular*,*multiple*viewpoints Feature pattern:*Sparse*patterns in 15x15 pixel ... A close variation on HMP is the multipath*sparse*coding method [124] , which effectively combines*multiple*sizes of smaller and medium-size patches and*multiple*layers of*sparse*coding into a single system ...##
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More algorithms for all-pairs shortest paths in weighted graphs

2007
*
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing - STOC '07
*

In the second part of the paper, we use fast

doi:10.1145/1250790.1250877
dblp:conf/stoc/Chan07
fatcat:hjvgkpode5cp7oarbre6fvynae
*matrix**multiplication*to obtain truly subcubic APSP algorithms for a large class of "geometrically weighted" graphs, where the weight of an edge is a function ... Second, Bansal and Williams [7] have announced a new purely combinatorial algorithm for Boolean*matrix**multiplication*which breaks the O(n 3 / log 2 n) barrier. ... In the author's previous paper [10] , we observe that the problem of computing the distance product of a*rectangular*n × d*matrix*and a*rectangular*d × n*matrix*can be viewed as a geometric range*searching*...##
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More Algorithms for All-Pairs Shortest Paths in Weighted Graphs

2010
*
SIAM journal on computing (Print)
*

In the second part of the paper, we use fast

doi:10.1137/08071990x
fatcat:g6nnaexymra7zcqynpdkbhaz6q
*matrix**multiplication*to obtain truly subcubic APSP algorithms for a large class of "geometrically weighted" graphs, where the weight of an edge is a function ... Second, Bansal and Williams [7] have announced a new purely combinatorial algorithm for Boolean*matrix**multiplication*which breaks the O(n 3 / log 2 n) barrier. ... In the author's previous paper [10] , we observe that the problem of computing the distance product of a*rectangular*n × d*matrix*and a*rectangular*d × n*matrix*can be viewed as a geometric range*searching*...##
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Sparse Regression via Range Counting
[article]

2019
*
arXiv
*
pre-print

Finally, we show how to adapt the approximation algorithm for the

arXiv:1908.00351v2
fatcat:a3hvkctvl5f6zombuercgxwzyy
*sparse*linear regression and*sparse*convex regression problems with the same running time, up to polylogarithmic factors. ... The*sparse*regression problem, also known as best subset selection problem, can be cast as follows: Given a set S of n points in R^d, a point y∈R^d, and an integer 2 ≤ k ≤ d, find an affine combination ... The triangle a 1 a 2 a 3*intersects*∆ if and only if a 3 is located in the*colored*region. Table 1 : 1 Results. ...##
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A Systematic Survey of General Sparse Matrix-Matrix Multiplication
[article]

2020
*
arXiv
*
pre-print

SpGEMM (General

arXiv:2002.11273v1
fatcat:5ppccisodvaevdhvfhawvjam5q
*Sparse**Matrix*-*Matrix**Multiplication*) has attracted much attention from researchers in fields of multigrid methods and graph analysis. ... Covered topics include SpGEMM applications, size prediction of result*matrix*,*matrix*partitioning and load balancing, result accumulating, and target architecture-oriented optimization. ... such as algebraic multigrid solvers [1] [2] [3] [4], triangle counting [5] [6] [7] [8] , multi-source breadthfirst*searching*[9] [10] [11] , the shortest path finding [12] ,*colored**intersecting*...##
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A Noise Robust Micro-Range Estimation Method for Precession Cone-Shaped Targets

2021
*
Remote Sensing
*

Trajectory Extraction

doi:10.3390/rs13091820
fatcat:wdxelmggmvdizakyw5q3f3ajmu
*via*the*Sparse*Signal Representation Algorithm In this section, the orthogonal matching pursuit (OMP) algorithm, which is a kind of*sparse*signal representation algorithm, is applied ... Besides, near the*intersection*of m-R curves, the*multiple*signal components are not separated for the limitation of resolution in the OMP algorithm. ...##
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Visual Object Tracking Robust to Illumination Variation Based on Hyperline Clustering

2019
*
Information
*

*Color*histogram-based trackers have obtained excellent performance against many challenging situations. ... However, since the appearance of

*color*is sensitive to illumination, they tend to achieve lower accuracy when illumination is severely variant throughout a sequence. ... In [20] , a

*sparse*representation based generative model is adopted to locate the target using a

*sparse*linear combination of the templates. ...

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