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Robustness of PSPACEcomplete sets
, 2008
"... We study the robustness of complete languages in PSPACE and prove that they are robust against Pselective sparse sets. Earlier similar results are known for EXPcomplete sets [3] and NPcomplete sets [7]. ..."
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Cited by 1 (1 self)
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We study the robustness of complete languages in PSPACE and prove that they are robust against Pselective sparse sets. Earlier similar results are known for EXPcomplete sets [3] and NPcomplete sets [7].
On the Structure of Complete Sets
 IN PROCEEDINGS 9TH STRUCTURE IN COMPLEXITY THEORY
, 1994
"... The many types of resource bounded reductions that are both object of study and research tool in structural complexity theory have given rise to a large variety of completeness notions. A complete set in a complexity class is a manageable object that represents the structure of the entire class. The ..."
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Cited by 19 (1 self)
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The many types of resource bounded reductions that are both object of study and research tool in structural complexity theory have given rise to a large variety of completeness notions. A complete set in a complexity class is a manageable object that represents the structure of the entire class
Properties of NPcomplete sets
 In Proceedings of the 19th IEEE Conference on Computational Complexity
, 2004
"... We study several properties of sets that are complete for NP. We prove that if L is an NPcomplete set and S � ⊇ L is a pselective sparse set, then L − S is ≤p mhard for NP. We demonstrate existence of a sparse set S ∈ DTIME(22n) such that for every L ∈ NP − P, L − S is not ≤p mhard for NP. Moreo ..."
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Cited by 7 (7 self)
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We study several properties of sets that are complete for NP. We prove that if L is an NPcomplete set and S � ⊇ L is a pselective sparse set, then L − S is ≤p mhard for NP. We demonstrate existence of a sparse set S ∈ DTIME(22n) such that for every L ∈ NP − P, L − S is not ≤p mhard for NP
SPLITTING NPCOMPLETE SETS
, 2006
"... We show that a set is mautoreducible if and only if it is mmitotic. This solves a long standing open question in a surprising way. As a consequence of this unconditional result and recent work by Gla6er et al., complete sets for all of the following complexity classes are mmitotic: NP, coNP, â ..."
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Cited by 2 (2 self)
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We show that a set is mautoreducible if and only if it is mmitotic. This solves a long standing open question in a surprising way. As a consequence of this unconditional result and recent work by Gla6er et al., complete sets for all of the following complexity classes are mmitotic: NP, coNP, â
Almost Complete Sets
, 2000
"... . We show that there is a set which is almost complete but not complete under polynomialtime manyone (pm) reductions for the class E of sets computable in deterministic time 2 lin . Here a set A in a complexity class C is almost complete for C under some reducibility r if the class of the p ..."
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Cited by 3 (2 self)
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. We show that there is a set which is almost complete but not complete under polynomialtime manyone (pm) reductions for the class E of sets computable in deterministic time 2 lin . Here a set A in a complexity class C is almost complete for C under some reducibility r if the class
A Singular Value Thresholding Algorithm for Matrix Completion
, 2008
"... This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task of reco ..."
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Cited by 553 (21 self)
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This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task
Exact Matrix Completion via Convex Optimization
, 2008
"... We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M. Can we complete the matrix and recover the entries that we have not seen? We show that one can perfe ..."
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Cited by 869 (26 self)
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We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M. Can we complete the matrix and recover the entries that we have not seen? We show that one can
Redundancy in Complete Sets
, 2005
"... ... We disprove the equivalence between autoreducibility and mitoticity for all polynomialtimebounded reducibilities between 3ttreducibility and Turingreducibility: There exists a sparse set in EXP that is polynomialtime 3ttautoreducible, but not weakly polynomialtime Tmitotic. In particula ..."
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Cited by 8 (6 self)
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... We disprove the equivalence between autoreducibility and mitoticity for all polynomialtimebounded reducibilities between 3ttreducibility and Turingreducibility: There exists a sparse set in EXP that is polynomialtime 3ttautoreducible, but not weakly polynomialtime T
The SimpleScalar tool set, version 2.0
 Computer Architecture News
, 1997
"... This report describes release 2.0 of the SimpleScalar tool set, a suite of free, publicly available simulation tools that offer both detailed and highperformance simulation of modern microprocessors. The new release offers more tools and capabilities, precompiled binaries, cleaner interfaces, bette ..."
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Cited by 1846 (43 self)
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, better documentation, easier installation, improved portability, and higher performance. This report contains a complete description of the tool set, including retrieval and installation instructions, a description of how to use the tools, a description of the target SimpleScalar architecture, and many
Results 1  10
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