International audienceWe will discuss challenges in building clusters for the Block Low-Rank (BLR) approach, for nodes inside separators appearing during the factorization of sparse matrices. We will illustrate limitations for methods that consider only intra-separators connectivity (i.e., k-way and recursive bisection) as well as methods focusing only on reducing the number of updates between separators. The new strategy we propose considers interactions between a separator and its children in the nested dissection. It allows reducing the computational cost of BLR, and the number of off-diagonal blocks. We demonstrate that this method enhances the BLR strategies in the sparse direct supernodal solver PaStiX, and discuss how it can be exten...
International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchic...
International audienceMatrices coming from elliptic Partial Differential Equations (PDEs) have been ...
We explore connections of low-rank matrix factorizations with interesting problems in data mining an...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
Solving sparse linear systems is a problem that arises in many scientific applications, and sparse d...
International audienceLow-rank compression techniques are very promising for reducing memory footpri...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchic...
International audienceIn this talk, we describe a preliminary fast direct solver using HODLR library...
Abstract Structured representation is of remarkable significance in subspace clusteri...
Submitted for publication to SIAMMatrices coming from elliptic Partial Differential Equations (PDEs)...
Sparse Subspace Clustering (SSC) and Low-Rank Representation (LRR) are both considered as the state-...
Sparse Subspace Clustering (SSC) and Low-Rank Representation (LRR) are both considered as the state-...
Inversion of sparse matrices with standard direct solve schemes is robust but computationally expens...
International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchic...
International audienceMatrices coming from elliptic Partial Differential Equations (PDEs) have been ...
We explore connections of low-rank matrix factorizations with interesting problems in data mining an...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
Solving sparse linear systems is a problem that arises in many scientific applications, and sparse d...
International audienceLow-rank compression techniques are very promising for reducing memory footpri...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchic...
International audienceIn this talk, we describe a preliminary fast direct solver using HODLR library...
Abstract Structured representation is of remarkable significance in subspace clusteri...
Submitted for publication to SIAMMatrices coming from elliptic Partial Differential Equations (PDEs)...
Sparse Subspace Clustering (SSC) and Low-Rank Representation (LRR) are both considered as the state-...
Sparse Subspace Clustering (SSC) and Low-Rank Representation (LRR) are both considered as the state-...
Inversion of sparse matrices with standard direct solve schemes is robust but computationally expens...
International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchic...
International audienceMatrices coming from elliptic Partial Differential Equations (PDEs) have been ...
We explore connections of low-rank matrix factorizations with interesting problems in data mining an...