Searching for authors named "Petros Drineas" – sorted by Relevance.
29 documents found, showing 1 through 10.
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Deterministic and randomized column selection algorithms for matrices
- …Abstract. Given a matrix A ∈ R m×n (m ≥ n) and an integer k (k ≪ n) we discuss deterministic and randomized algorithms for selecting the k “most linearly independent ” columns of A. After summarizing previous deterministic and randomized algorithms for this task, we present a hybrid approach. First,…
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Concurrent Fault Detection in Random Combinational Logic
- …We discuss a non-intrusive methodology for concurrent fault detection in random combinational logic. The proposed method is similar to duplication, wherein a replica of the circuit acts as a predictor that immediately detects potential faults by comparison to the original circuit. However, instead o…
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Non-Intrusive Concurrent Error Detection in FSMs through State/Output Compaction and Monitoring via Parity Trees
- …We discuss a non-intrusive methodology for concurrent error detection in FSMs. The proposed method is based on compaction and monitoring of the state/output bits of an FSM via parity trees. While errors may affect more than one state/output bit, not all combinations of state/output bits constitute p…
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Fast Monte-Carlo Algorithms for Approximate Matrix Multiplication
- …Given an m n matrix A and an n p matrix B, we present 2 simple and intuitive algorithms to compute an approximation P to the product A B, with provable bounds for the norm of the \error matrix" P A B. Both algorithms run in O(mp+mn+np) time. In both algorithms, we randomly pick s = O(1) columns …
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Pass Efficient Algorithms for Approximating Large Matrices
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Independent Test Sequence Compaction through Integer Programming
- …We discuss the compaction of independent test sequences for sequential circuits. Our first contribution is the formulation of this problem as an integer program, which we then solve through a well-known method employing linear programming relaxation and randomized rounding. The key contribution of t…
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Pass Ecient Algorithms for Approximating Large Matrices
- …this paper is stated and proved in this section. For any mn matrix A, suppose C is an m c matrix formed by a random subset of c columns of A, picked in c independent identical trials; in each trial one of the n columns of A is picked with the probability of picking column j being q j . The a…
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Fast Monte-Carlo Algorithms for Approximate Matrix Multiplication
- …Given an m n matrix A and an n p matrix B, we present 2 simple and intuitive algorithms to compute an approximation P to the product A B, with provable bounds for the norm of the "error matrix" P B. Both algorithms run in O(mp+mn+np) time. In both algorithms, we randomly pick s = O(1) co…
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Sampling algorithms for `2 regression and applications
- …S. Muthukrishnan z…
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On the Nystr"om method for approximating a Gram matrix for improved kernel-based learning
- …CW k C T, where C is a matrix consisting of a small number c of columns of G and Wk is the best rank-k approximation to W, the matrix formed by the intersection between those c columns of G and the corresponding c rows of G. An important aspect of the algorithm is the probability distribution used t…
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