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CVPR
2012
IEEE
6 years 11 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
AAAI
2011
7 years 9 months ago
Sparse Matrix-Variate t Process Blockmodels
We consider the problem of modeling network interactions and identifying latent groups of network nodes. This problem is challenging due to the facts i) that the network nodes are...
Zenglin Xu, Feng Yan, Yuan Qi
PC
2008
111views Management» more  PC 2008»
8 years 9 months ago
A partitioning algorithm for block-diagonal matrices with overlap
We present a graph partitioning algorithm that aims at partitioning a sparse matrix into a block-diagonal form, such that any two consecutive blocks overlap. We denote this form o...
Guy Antoine Atenekeng Kahou, Laura Grigori, Masha ...
AC
2008
Springer
8 years 9 months ago
Distributed Sparse Matrices for Very High Level Languages
Sparse matrices are first class objects in many VHLLs (very high level languages) used for scientific computing. They are a basic building block for various numerical and combinat...
John R. Gilbert, Steve Reinhardt, Viral Shah
DATESO
2004
165views Database» more  DATESO 2004»
8 years 10 months ago
Multi-dimensional Sparse Matrix Storage
Large sparse matrices play important role in many modern information retrieval methods. These methods, such as clustering, latent semantic indexing, performs huge number of computa...
Jiri Dvorský, Michal Krátký
ESANN
2007
8 years 10 months ago
Collaborative Filtering with interlaced Generalized Linear Models
Collaborative Filtering (CF) aims at finding patterns in a sparse matrix of contingency. It can be used for example to mine the ratings given by users on a set of items. In this p...
Nicolas Delannay, Michel Verleysen
FCCM
2007
IEEE
165views VLSI» more  FCCM 2007»
8 years 11 months ago
Sparse Matrix-Vector Multiplication Design on FPGAs
Creating a high throughput sparse matrix vector multiplication (SpMxV) implementation depends on a balanced system design. In this paper, we introduce the innovative SpMxV Solver ...
Junqing Sun, Gregory D. Peterson, Olaf O. Storaasl...
CF
2005
ACM
8 years 11 months ago
Sparse matrix storage revisited
In this paper, we consider alternate ways of storing a sparse matrix and their effect on computational speed. They involve keeping both the indices and the non-zero elements in t...
Malik Silva
ICS
1997
Tsinghua U.
9 years 1 months ago
Sparse Code Generation for Imperfectly Nested Loops with Dependences
Standard restructuring compiler tools are based on polyhedral algebra and cannot be used to analyze or restructure sparse matrix codes. We have recently shown that tools based on ...
Vladimir Kotlyar, Keshav Pingali
EUROPAR
1997
Springer
9 years 1 months ago
A Relational Approach to the Compilation of Sparse Matrix Programs
Abstract. We present a relational algebra based framework for compiling e cient sparse matrix code from dense DO-ANY loops and a speci cation of the representation of the sparse ma...
Vladimir Kotlyar, Keshav Pingali, Paul Stodghill
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