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Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for ...
This paper investigates rate-optimal estimation of the volatility matrix of a high-dimensional Itô process observed with measurement errors at discrete time points. The minimax rate of convergence is ...
We introduce a constrained empirical loss minimization framework for estimating highdimensional sparse precision matrices and propose a new loss function, called the D-trace loss, for that purpose. A ...
A combined sparse matrix and incomplete factorial screens, samples pH 3.5 to 8.5, low ionic strength, high ionic strength and mixed polymer/salt conditions and halides for potential phasing (see ...
Real PIM systems can provide high levels of parallelism, large aggregate memory bandwidth and low memory access latency, thereby being a good fit to accelerate the widely-used, memory-bound Sparse ...